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Model: huihui-ai/Huihui-MoE-1B-A0.6B Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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base_model:
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- Qwen/Qwen3-0.6B
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- suayptalha/Qwen3-0.6B-Code-Expert
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- suayptalha/Qwen3-0.6B-Math-Expert
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- suayptalha/Qwen3-0.6B-Medical-Expert
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library_name: transformers
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license_link: https://huggingface.co/Qwen/Qwen3-0.6B/blob/main/LICENSE
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pipeline_tag: text-generation
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tags:
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- moe
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---
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# huihui-ai/Huihui-MoE-1B-A0.6B
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## Model Overview
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Huihui-MoE-1B-A0.6B is a **Mixture of Experts (MoE)** language model developed by **huihui.ai**, built upon the **[Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B)** base model. It enhances the standard Transformer architecture by replacing MLP layers with MoE layers, each containing 3 experts, to achieve high performance with efficient inference. The model is designed for natural language processing tasks, including text generation, question answering, and conversational applications.
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This version does not support ollama because tie_word_embeddings=True results in the absence of lm_head parameters being saved; therefore, ollama cannot be used. If ollama support is required, please choose the latest version [huihui-ai/Huihui-MoE-1.2B-A0.6B](https://huggingface.co/huihui-ai/Huihui-MoE-1.2B-A0.6B).
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- **Architecture**: Qwen3MoeForCausalLM model with 3 experts per layer (num_experts=3), activating 1 expert per token (num_experts_per_tok=1).
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- **Total Parameters**: ~1.1 billion (1B)
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- **Activated Parameters**: ~0.62 billion (0.6B) during inference, comparable to Qwen3-0.6B
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- **Developer**: huihui.ai
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- **Release Date**: June 2025
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- **License**: Inherits the license of the Qwen3 base model (apache-2.0)
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## Expert Models:
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### Coding:
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[suayptalha/Qwen3-0.6B-Code-Expert](https://huggingface.co/suayptalha/Qwen3-0.6B-Code-Expert)
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This model was fully fine-tuned with BF16 on first 20k rows of `nvidia/OpenCodeReasoning` dataset for 1 epoch.
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### Math:
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[suayptalha/Qwen3-0.6B-Math-Expert](https://huggingface.co/suayptalha/Qwen3-0.6B-Math-Expert)
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This model was fully fine-tuned with BF16 on entire `unsloth/OpenMathReasoning-mini` dataset for 1 epoch.
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### Medical:
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[suayptalha/Qwen3-0.6B-Medical-Expert](https://huggingface.co/suayptalha/Qwen3-0.6B-Medical-Expert)
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This model was fully fine-tuned with BF16 on first 20k rows of `FreedomIntelligence/medical-o1-reasoning-SFT` dataset for 1 epoch.
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### Instruction Following:
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[Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B)
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`Qwen/Qwen3-0.6B` model was directly used for this expert, no fine-tune was applied.
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## Training
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- **Base Model**: Qwen3-0.6B, pre-trained by the Qwen team, Experts, pre-trained by the Suayptalha team.
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- **Conversion**: The model copies embeddings, self-attention, and normalization weights from Qwen3-0.6B, replacing MLP layers with MoE layers (3 experts). Gating weights are randomly initialized.
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- **Fine-Tuning**: Not fine-tuned; users are recommended to fine-tune for specific tasks to optimize expert routing. The fine-tuned version is already available and can be referred to as [huihui-ai/Huihui-MoE-1B-A0.6B-SFT](https://huggingface.co/huihui-ai/Huihui-MoE-1B-A0.6B-SFT).
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## Usage
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```
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from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, TextStreamer
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import torch
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import os
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import signal
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cpu_count = os.cpu_count()
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print(f"Number of CPU cores in the system: {cpu_count}")
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half_cpu_count = cpu_count // 2
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os.environ["MKL_NUM_THREADS"] = str(half_cpu_count)
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os.environ["OMP_NUM_THREADS"] = str(half_cpu_count)
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torch.set_num_threads(half_cpu_count)
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print(f"PyTorch threads: {torch.get_num_threads()}")
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print(f"MKL threads: {os.getenv('MKL_NUM_THREADS')}")
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print(f"OMP threads: {os.getenv('OMP_NUM_THREADS')}")
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# Load the model and tokenizer
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NEW_MODEL_ID = "huihui-ai/Huihui-MoE-1B-A0.6B"
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print(f"Load Model {NEW_MODEL_ID} ... ")
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quant_config_4 = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_compute_dtype=torch.bfloat16,
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bnb_4bit_use_double_quant=True,
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llm_int8_enable_fp32_cpu_offload=True,
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)
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model = AutoModelForCausalLM.from_pretrained(
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NEW_MODEL_ID,
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device_map="auto",
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trust_remote_code=True,
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#quantization_config=quant_config_4,
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torch_dtype=torch.bfloat16
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)
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tokenizer = AutoTokenizer.from_pretrained(NEW_MODEL_ID, trust_remote_code=True)
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if tokenizer.pad_token is None:
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tokenizer.pad_token = tokenizer.eos_token
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tokenizer.pad_token_id = tokenizer.eos_token_id
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initial_messages = [{"role": "system", "content": "You are a helpful assistant."}]
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messages = initial_messages.copy()
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enable_thinking = True
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skip_prompt=True
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skip_special_tokens=True
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class CustomTextStreamer(TextStreamer):
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def __init__(self, tokenizer, skip_prompt=True, skip_special_tokens=True):
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super().__init__(tokenizer, skip_prompt=skip_prompt, skip_special_tokens=skip_special_tokens)
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self.generated_text = ""
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self.stop_flag = False
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def on_finalized_text(self, text: str, stream_end: bool = False):
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self.generated_text += text
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print(text, end="", flush=True)
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if self.stop_flag:
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raise StopIteration
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def stop_generation(self):
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self.stop_flag = True
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def generate_stream(model, tokenizer, messages, enable_thinking, skip_prompt, skip_special_tokens, max_new_tokens):
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input_ids = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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enable_thinking = enable_thinking,
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add_generation_prompt=True,
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return_tensors="pt"
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)
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attention_mask = torch.ones_like(input_ids, dtype=torch.long)
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tokens = input_ids.to(model.device)
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attention_mask = attention_mask.to(model.device)
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streamer = CustomTextStreamer(tokenizer, skip_prompt=skip_prompt, skip_special_tokens=skip_special_tokens)
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def signal_handler(sig, frame):
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streamer.stop_generation()
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print("\n[Generation stopped by user with Ctrl+C]")
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signal.signal(signal.SIGINT, signal_handler)
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print("Response: ", end="", flush=True)
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try:
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generated_ids = model.generate(
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tokens,
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attention_mask=attention_mask,
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#use_cache=False,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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pad_token_id=tokenizer.pad_token_id,
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streamer=streamer
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)
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del generated_ids
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except StopIteration:
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print("\n[Stopped by user]")
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del input_ids, attention_mask
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torch.cuda.empty_cache()
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signal.signal(signal.SIGINT, signal.SIG_DFL)
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return streamer.generated_text, streamer.stop_flag
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while True:
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user_input = input("User: ").strip()
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if user_input.lower() == "/exit":
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print("Exiting chat.")
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break
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if user_input.lower() == "/clear":
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messages = initial_messages.copy()
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print("Chat history cleared. Starting a new conversation.")
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continue
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if user_input.lower() == "/nothink":
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if enable_thinking:
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enable_thinking = False
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print("Thinking = False.")
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else:
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enable_thinking = True
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print("Thinking = True.")
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continue
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if user_input.lower() == "/skip_prompt":
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if skip_prompt:
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skip_prompt = False
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print("skip_prompt = False.")
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else:
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skip_prompt = True
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print("skip_prompt = True.")
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continue
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if user_input.lower() == "/skip_special_tokens":
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if skip_special_tokens:
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skip_special_tokens = False
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print("skip_special_tokens = False.")
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else:
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skip_special_tokens = True
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print("skip_special_tokens = True.")
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continue
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if not user_input:
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print("Input cannot be empty. Please enter something.")
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continue
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messages.append({"role": "user", "content": user_input})
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response, stop_flag = generate_stream(model, tokenizer, messages, enable_thinking, skip_prompt, skip_special_tokens, 14192)
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print("", flush=True)
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if stop_flag:
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continue
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messages.append({"role": "assistant", "content": response})
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```
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## Applications
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- **Text Generation: Articles**, dialogues, and creative writing.
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- **Question Answering**: Information retrieval and query resolution.
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- **Conversational AI**: Multi-turn dialogues for chatbots.
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- **Research**: Exploration of MoE architectures and efficient model scaling.
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## Limitations
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- **Fine-Tuning Required**: Randomly initialized gating weights may lead to suboptimal expert utilization without fine-tuning.
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- **Compatibility**: Developed with transformers 4.52.4; ensure matching versions to avoid loading issues.
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- **Inference Speed**: While efficient for an MoE model, performance depends on hardware (GPU recommended).
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## Ethical Considerations
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- **Bias**: Inherits potential biases from the Qwen3-0.6B base model; users should evaluate outputs for fairness.
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- **Usage**: Intended for research and responsible applications; avoid generating harmful or misleading content.
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## Contact
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- **Developer**: huihui.ai
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- **Repository**: huihui-ai/Huihui-MoE-1B-A0.6B (available locally or on Hugging Face)
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- **Issues**: Report bugs or request features via the repository or please send an email to support@huihui.ai
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## Acknowledgments
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- Built upon the Qwen3-0.6B model by the Qwen team.
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- Built upon the Experts model by the Suayptalha team.
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- Powered by the Hugging Face transformers library.
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28
added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set content = message.content %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in message.content %}
|
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{%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
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{%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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||||
{%- endif %}
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||||
{%- else %}
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||||
{{- '<|im_start|>' + message.role + '\n' + content }}
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||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
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{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
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||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
38
config.json
Normal file
38
config.json
Normal file
@@ -0,0 +1,38 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3MoeForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"decoder_sparse_step": 1,
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 1024,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 3072,
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 28,
|
||||
"mlp_only_layers": [],
|
||||
"model_type": "qwen3_moe",
|
||||
"moe_intermediate_size": 3072,
|
||||
"norm_topk_prob": true,
|
||||
"num_attention_heads": 16,
|
||||
"num_experts": 3,
|
||||
"num_experts_per_tok": 1,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 8,
|
||||
"output_router_logits": false,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000,
|
||||
"router_aux_loss_coef": 0.001,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.52.4",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
6
generation_config.json
Normal file
6
generation_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"transformers_version": "4.52.4"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:e893bd29c30948c66b7bb6da4ede05684aa35eea99c8b2a07bfd8a9aa56e1b17
|
||||
size 2249296512
|
||||
510
model_params.txt
Normal file
510
model_params.txt
Normal file
@@ -0,0 +1,510 @@
|
||||
Model Parameter Distribution:
|
||||
------------------------------------------------------------
|
||||
model.embed_tokens.weight: 155,582,464 parameters, device cuda:0
|
||||
model.layers.0.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.0.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.0.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.0.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.0.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.0.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.0.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.0.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.0.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.1.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.1.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.1.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.1.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.1.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.1.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.1.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.1.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.1.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.2.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.2.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.2.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.2.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.2.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.2.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.2.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.2.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.2.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.3.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.3.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.3.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.3.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.3.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.3.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.3.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
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|
||||
model.layers.3.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.3.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.3.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.4.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.4.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.4.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.4.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.4.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.4.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.4.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.4.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.4.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.5.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.5.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.5.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.5.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.5.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.5.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.5.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.5.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.5.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.6.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.6.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.6.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.6.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.6.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.6.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.6.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.6.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.6.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.6.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
model.layers.6.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.6.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
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|
||||
model.layers.7.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.7.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.7.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.7.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.7.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
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|
||||
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|
||||
model.layers.7.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
model.layers.8.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
model.layers.8.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
model.layers.9.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
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|
||||
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model.layers.21.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.21.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.21.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.21.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.22.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.22.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.22.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.22.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.22.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.22.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.22.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.22.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.22.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.23.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.23.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.23.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.23.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.23.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.23.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.23.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.23.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.23.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.24.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.24.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.24.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.24.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.24.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.24.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.24.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.24.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.24.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.25.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.25.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.25.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.25.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.25.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.25.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.25.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.25.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.25.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.26.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.26.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.26.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.26.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.26.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.26.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.26.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.26.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.26.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.27.self_attn.q_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.27.self_attn.k_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.27.self_attn.v_proj.weight: 1,048,576 parameters, device cuda:0
|
||||
model.layers.27.self_attn.o_proj.weight: 2,097,152 parameters, device cuda:0
|
||||
model.layers.27.self_attn.q_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.27.self_attn.k_norm.weight: 128 parameters, device cuda:0
|
||||
model.layers.27.mlp.gate.weight: 3,072 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.0.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.0.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.0.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.1.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.1.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.1.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.2.gate_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.2.up_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.mlp.experts.2.down_proj.weight: 3,145,728 parameters, device cuda:0
|
||||
model.layers.27.input_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.layers.27.post_attention_layernorm.weight: 1,024 parameters, device cuda:0
|
||||
model.norm.weight: 1,024 parameters, device cuda:0
|
||||
------------------------------------------------------------
|
||||
Total Model Parameter Count:1,124,618,240
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user