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Model: huihui-ai/DeepSeek-R1-Distill-Qwen-1.5B-abliterated Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- abliterated
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- uncensored
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library_name: transformers
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---
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# huihui-ai/DeepSeek-R1-Distill-Qwen-1.5B-abliterated
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This is an uncensored version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) reasoning model that has been post-trained by huihui-ai.
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Please refer to [SFT with Unsloth](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_(7B)-Alpaca.ipynb#scrollTo=2ejIt2xSNKKp) for the training method.
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This is a test conducted through fine-tuning for ablation to achieve the purpose of being uncensored, and the test results met the expected outcomes.
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## Use with ollama
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You can use [huihui_ai/deepseek-r1-abliterated](https://ollama.com/huihui_ai/deepseek-r1-abliterated) directly
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```
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ollama run huihui_ai/deepseek-r1-abliterated:1.5b
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```
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## Use with transformers
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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/DeepSeek-R1-Distill-Qwen-1.5B-abliterated"
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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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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, 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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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=True, skip_special_tokens=True)
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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("\nUser: ").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 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, 8192)
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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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config.json
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
|
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"max_position_embeddings": 131072,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 12,
|
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"num_hidden_layers": 28,
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"num_key_value_heads": 2,
|
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"pad_token_id": 151654,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.51.1",
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"unsloth_version": "2025.3.19",
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"use_cache": true,
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"use_mrope": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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generation_config.json
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{
|
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"_from_model_config": true,
|
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"bos_token_id": 151646,
|
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"do_sample": true,
|
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"eos_token_id": 151643,
|
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"max_length": 131072,
|
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"pad_token_id": 151654,
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"temperature": 0.6,
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"top_p": 0.95,
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"transformers_version": "4.51.1"
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}
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3
model.safetensors
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3
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d464b76b5acb42925d37ffd8f46f71af9163505587f2a85ff100b8697e5fa599
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size 3554214752
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special_tokens_map.json
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<｜begin▁of▁sentence｜>",
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||||
"lstrip": false,
|
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"normalized": false,
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"single_word": false
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"eos_token": {
|
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|
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"lstrip": false,
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"normalized": false,
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"single_word": false
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},
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"pad_token": "<|vision_pad|>"
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}
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3
tokenizer.json
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3
tokenizer.json
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version https://git-lfs.github.com/spec/v1
|
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oid sha256:e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
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size 11422778
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196
tokenizer_config.json
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tokenizer_config.json
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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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|
||||
"bos_token": "<｜begin▁of▁sentence｜>",
|
||||
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<｜end▁of▁sentence｜>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"padding_side": "left",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizerFast",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user