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Model: prithivMLmods/Primus-Optima-QwenKV-1.54B Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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pipeline_tag: text-generation
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license: apache-2.0
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language:
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- en
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- zh
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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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- Code
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- Math
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- RL
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- R1
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---
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# **Primus-Optima-QwenKV-1.54B**
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> **Primus-Optima-QwenKV-1.54B** is an **experimental chain-of-thought reasoning and code generation model**, built by combining the strengths of two sources:
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>
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> - **DeepSeek R1 (distilled 1.5B)** for strong math and coding reasoning.
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> - **Qwen2.5-0.5B**, fine-tuned with **Process Reward Models (PRM)** to boost structured step-by-step outputs in math and logic.
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This hybrid design results in a **bilingual, high-precision model** with enhanced **reasoning depth**, **multi-step clarity**, and **lightweight adaptability** for math and code applications.
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## **Key Features**
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1. **Chain-of-Thought Reasoning for Math + Code**
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Designed to produce human-like intermediate steps in both math and programming problems — useful for education, tutoring, and technical assistants.
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2. **Hybrid Architecture (Reasoning + Reward-Guided Fine-Tuning)**
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Combines **DeepSeek R1’s** distilled capabilities with **Qwen2.5-0.5B**'s reward-optimized reasoning for structured, goal-driven outputs.
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3. **Multilingual Capabilities (English + 中文)**
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Fluent and accurate in both English and Simplified Chinese, making it suitable for diverse learning and development environments.
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4. **Coder Experimental Mode**
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Able to solve algorithmic tasks, complete functions, and offer code walkthroughs using the same step-by-step format as it does for math.
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5. **Lightweight Yet Capable (1.54B)**
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With just 1.54B parameters, it is efficient for local deployments while offering surprisingly strong performance on STEM and programming tasks.
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## **Quickstart with Transformers**
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "prithivMLmods/Primus-Optima-QwenKV-1.54B"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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prompt = "Write a Python function to compute factorial using recursion."
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messages = [
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{"role": "system", "content": "You are an expert tutor in math and programming, explaining step-by-step."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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```
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## **Intended Use**
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- **Math & Programming Tutors**: Assist students with logic-driven step-by-step explanations.
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- **Bilingual STEM Apps**: Ideal for dual-language math or coding environments.
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- **Competitive Reasoning Tools**: Suited for reasoning-intensive tasks like Olympiad prep, technical quizzes, and programming challenges.
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- **On-Device LLMs**: Lightweight enough for web or embedded applications needing real-time reasoning.
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## **Limitations**
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1. **Experimental Nature**:
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This is a hybrid research model; performance may vary across general or creative domains.
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2. **Size Constraints**:
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As a 1.54B parameter model, extremely complex reasoning tasks may challenge its capabilities.
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3. **Bias & Generalization**:
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Inherits biases from both DeepSeek R1 and Qwen2.5. Use caution in high-stakes or sensitive applications.
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4. **Prompt Engineering Required**:
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Structured prompts with clear questions yield the best results, especially for multi-step problems.
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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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"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": 32768,
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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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"rms_norm_eps": 1e-06,
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"tie_word_embeddings": true,
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"torch_dtype": "float32",
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"transformers_version": "4.50.0.dev0",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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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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|
||||
}
|
||||
}
|
||||
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
|
||||
},
|
||||
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|
||||
"content": "<|fim_pad|>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9ffb4bd5c40b82c8e9ee9be5eb1632ad555eb42250ccc4eece6325a37e78ba1a
|
||||
size 11421895
|
||||
208
tokenizer_config.json
Normal file
208
tokenizer_config.json
Normal file
@@ -0,0 +1,208 @@
|
||||
{
|
||||
"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|>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
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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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|
||||
"special": true
|
||||
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|
||||
"151652": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
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|
||||
"content": "<|vision_pad|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
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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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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
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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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
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|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
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|
||||
"<|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,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# 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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|fim_pad|>",
|
||||
"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