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Model: inarikami/DeepSeek-R1-Distill-Qwen-32B-AWQ Source: Original Platform
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README.md
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README.md
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---
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license: mit
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pipeline_tag: text-generation
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tags:
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- code
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- deepseek_v3
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- qwen
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- int4
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- conversational
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
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---
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# DeepSeek-R1-Distill-Qwen-32B-AWQ wint4
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Distillation of DeepSeek-R1 to Qwen 32B, quantized using AWQ to wint4. It fits on any 24GB VRAM GPU or 32GB URAM device!
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## MMLU-PRO
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The MMLU-PRO dataset evaluates subjects across 14 distinct fields using a 5-shot accuracy measurement. Each task assesses models following the methodology of the original MMLU implementation, with each having ten possible choices.
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### Measure
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- **Accuracy**: Evaluated as "exact_match"
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### Shots
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- **Shots**: 5-shot
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### Tasks
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| Tasks | Filter | n-shot | Metric | Value | Stderr |
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|------------------|---------------|--------|-------------|--------|--------|
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| mmlu_pro | custom-extract| | exact_match | 0.5875 | 0.0044 |
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| biology | custom-extract| 5 | exact_match | 0.7978 | 0.0150 |
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| business | custom-extract| 5 | exact_match | 0.5982 | 0.0175 |
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| chemistry | custom-extract| 5 | exact_match | 0.4691 | 0.0148 |
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| computer_science | custom-extract| 5 | exact_match | 0.6122 | 0.0241 |
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| economics | custom-extract| 5 | exact_match | 0.7346 | 0.0152 |
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| engineering | custom-extract| 5 | exact_match | 0.3891 | 0.0157 |
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| health | custom-extract| 5 | exact_match | 0.6345 | 0.0168 |
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| history | custom-extract| 5 | exact_match | 0.6168 | 0.0249 |
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| law | custom-extract| 5 | exact_match | 0.4596 | 0.0150 |
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| math | custom-extract| 5 | exact_match | 0.6425 | 0.0130 |
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| other | custom-extract| 5 | exact_match | 0.6223 | 0.0160 |
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| philosophy | custom-extract| 5 | exact_match | 0.5731 | 0.0222 |
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| physics | custom-extract| 5 | exact_match | 0.5073 | 0.0139 |
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| psychology | custom-extract| 5 | exact_match | 0.7494 | 0.0154 |
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### Groups
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| Groups | Filter | n-shot | Metric | Value | Stderr |
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|----------|---------------|--------|-------------|--------|--------|
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| mmlu_pro | custom-extract| | exact_match | 0.5875 | 0.0044 |
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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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"quantization_config": {
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"bits": 4,
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"quant_method": "awq",
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"version": "gemm",
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"zero_point": true
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"transformers_version": "4.47.1",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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|
"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
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"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|>'}}{% endif %}",
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|end▁of▁sentence|>",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"legacy": true,
|
||||||
|
"model_max_length": 16384,
|
||||||
|
"pad_token": "<|end▁of▁sentence|>",
|
||||||
|
"sp_model_kwargs": {},
|
||||||
|
"tokenizer_class": "LlamaTokenizer",
|
||||||
|
"unk_token": null,
|
||||||
|
"use_default_system_prompt": false
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user