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Model: Vishva007/Qwen3-4B-Instruct-2507-W4A16-AutoRound-AWQ Source: Original Platform
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.gitattributes
vendored
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114
README.md
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README.md
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---
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base_model: Qwen/Qwen3-4B-Instruct-2507
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library_name: transformers
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license: apache-2.0
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tags:
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- awq
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- qwen
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- qwen3
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- quantization
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- 4-bit
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- vllm
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pipeline_tag: text-generation
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model_type: qwen2
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---
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# Qwen3-4B-Instruct-2507-W4A16-AutoRound-AWQ
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## Model Overview
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This is the **AWQ (Activation-aware Weight Quantization)** version of **[Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)**.
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It was generated using **Intel's AutoRound** algorithm, which optimizes the weight rounding to minimize quantization loss. This ensures superior accuracy compared to standard AWQ conversion methods.
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### Key Features
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- **4-bit Inference**: Runs efficiently on Nvidia GPUs.
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- **High Accuracy**: Tuned for 1000 iterations using AutoRound.
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- **Broad Compatibility**: Works natively with `vLLM`, `TGI`, and `Transformers`.
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## Specifications
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- **Scheme**: W4A16 (4-bit weights, 16-bit activations)
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- **Group Size**: 128
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- **Symmetric**: True
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- **Calibration Data**: 512 samples
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- **Format**: AutoAWQ (Compatible with standard AWQ kernels)
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## Usage
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### Option A: Using vLLM (Recommended for Speed)
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This model is optimized for high-throughput serving with vLLM.
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```bash
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pip install vllm
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```
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```python
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from vllm import LLM, SamplingParams
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model_id = "Vishva007/Qwen3-4B-Instruct-2507-W4A16-AutoRound-AWQ"
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llm = LLM(
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model=model_id,
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quantization="awq",
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dtype="half",
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max_model_len=8192,
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gpu_memory_utilization=0.90
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)
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prompts = ["What is the capital of France?"]
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sampling_params = SamplingParams(temperature=0.7, top_p=0.8)
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outputs = llm.generate(prompts, sampling_params)
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for output in outputs:
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print(output.outputs.text)
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```
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### Option B: Using Hugging Face Transformers
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```bash
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pip install autoawq transformers
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```
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "Vishva007/Qwen3-4B-Instruct-2507-W4A16-AutoRound-AWQ"
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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prompt = "Write a python function to reverse a string."
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messages = [{"role": "user", "content": prompt}]
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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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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=256)
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print(tokenizer.decode(outputs, skip_special_tokens=True))
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```
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## Benchmark & Performance
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This model maintains the strong performance of the Qwen3-4B-Instruct-2507 base model, including its updated reasoning and coding capabilities.
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| Model | Format | VRAM (Est.) |
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| :--- | :--- | :--- |
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| Qwen3-4B-Instruct (BF16) | Original | ~9 GB |
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| **Qwen3-4B-Instruct (AWQ)** | **4-bit** | **~3.5 GB** |
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## Citation
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```bibtex
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@misc{qwen3technicalreport,
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title={Qwen3 Technical Report},
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author={Qwen Team},
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year={2025},
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eprint={2505.09388},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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added_tokens.json
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added_tokens.json
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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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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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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' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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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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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"dtype": "float16",
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"layer_types": [
|
||||
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"full_attention",
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"full_attention",
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|
||||
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|
||||
"full_attention"
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],
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||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"quantization_config": {
|
||||
"autoround_version": "0.9.7",
|
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"batch_size": 4,
|
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"bits": 4,
|
||||
"data_type": "int",
|
||||
"group_size": 128,
|
||||
"iters": 1000,
|
||||
"modules_to_not_convert": [],
|
||||
"nsamples": 512,
|
||||
"provider": "auto-round",
|
||||
"quant_method": "awq",
|
||||
"sym": true,
|
||||
"version": "gemm",
|
||||
"zero_point": false
|
||||
},
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.6",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
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generation_config.json
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generation_config.json
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{
|
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"bos_token_id": 151643,
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"do_sample": 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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"temperature": 0.7,
|
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"top_k": 20,
|
||||
"top_p": 0.8,
|
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"transformers_version": "4.57.6"
|
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}
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merges.txt
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151388
merges.txt
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Load Diff
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f5a0a5788f051a66733bb8a4ee34970eecbbde5535059013160b4019449ecf8
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size 2666027480
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quantization_config.json
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quantization_config.json
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{
|
||||
"bits": 4,
|
||||
"group_size": 128,
|
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"sym": true,
|
||||
"data_type": "int",
|
||||
"batch_size": 4,
|
||||
"iters": 1000,
|
||||
"nsamples": 512,
|
||||
"autoround_version": "0.9.7",
|
||||
"provider": "auto-round",
|
||||
"quant_method": "awq",
|
||||
"zero_point": false,
|
||||
"version": "gemm",
|
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"modules_to_not_convert": []
|
||||
}
|
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special_tokens_map.json
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special_tokens_map.json
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{
|
||||
"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
|
||||
}
|
||||
}
|
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BIN
tokenizer.json
(Stored with Git LFS)
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BIN
tokenizer.json
(Stored with Git LFS)
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tokenizer_config.json
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tokenizer_config.json
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||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
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|
||||
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|
||||
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|
||||
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|
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"single_word": false,
|
||||
"special": true
|
||||
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|
||||
"151644": {
|
||||
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|
||||
"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,
|
||||
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|
||||
"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": 1010000,
|
||||
"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