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--- |
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tags: |
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- gptq |
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- 4bit |
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- int4 |
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- gptqmodel |
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- modelcloud |
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- llama-3.1 |
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- 8b |
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- instruct |
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license: llama3.1 |
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--- |
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This model has been quantized using [GPTQModel](https://github.com/ModelCloud/GPTQModel). |
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- **bits**: 4 |
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- **group_size**: 128 |
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- **desc_act**: true |
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- **static_groups**: false |
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- **sym**: true |
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- **lm_head**: false |
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- **damp_percent**: 0.005 |
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- **true_sequential**: true |
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- **model_name_or_path**: "" |
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- **model_file_base_name**: "model" |
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- **quant_method**: "gptq" |
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- **checkpoint_format**: "gptq" |
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- **meta**： |
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- **quantizer**: "gptqmodel:0.9.9-dev0" |
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## Example: |
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```python |
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from transformers import AutoTokenizer |
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from gptqmodel import GPTQModel |
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model_name = "ModelCloud/Meta-Llama-3.1-8B-Instruct-gptq-4bit" |
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prompt = [{"role": "user", "content": "I am in Shanghai, preparing to visit the natural history museum. Can you tell me the best way to"}] |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = GPTQModel.from_quantized(model_name) |
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input_tensor = tokenizer.apply_chat_template(prompt, add_generation_prompt=True, return_tensors="pt") |
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outputs = model.generate(input_ids=input_tensor.to(model.device), max_new_tokens=100) |
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result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True) |
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print(result) |
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``` |
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## lm-eval benchmark |
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``` |
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| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |
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|---------------------------------------|------:|------|-----:|----------|---|-----:|---|-----:| |
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|arc_challenge | 1|none | 0|acc |↑ |0.4889|± |0.0146| |
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| | |none | 0|acc_norm |↑ |0.5265|± |0.0146| |
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|arc_easy | 1|none | 0|acc |↑ |0.7908|± |0.0083| |
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| | |none | 0|acc_norm |↑ |0.7702|± |0.0086| |
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|boolq | 2|none | 0|acc |↑ |0.8404|± |0.0064| |
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|hellaswag | 1|none | 0|acc |↑ |0.5748|± |0.0049| |
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| | |none | 0|acc_norm |↑ |0.7718|± |0.0042| |
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|lambada_openai | 1|none | 0|acc |↑ |0.7110|± |0.0063| |
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| | |none | 0|perplexity|↓ |4.0554|± |0.0955| |
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|mmlu | 1|none | |acc |↑ |0.6411|± |0.0038| |
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| - humanities | 1|none | |acc |↑ |0.5896|± |0.0068| |
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| - formal_logic | 0|none | 0|acc |↑ |0.4762|± |0.0447| |
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| - high_school_european_history | 0|none | 0|acc |↑ |0.7273|± |0.0348| |
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| - high_school_us_history | 0|none | 0|acc |↑ |0.8088|± |0.0276| |
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| - high_school_world_history | 0|none | 0|acc |↑ |0.8270|± |0.0246| |
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| - international_law | 0|none | 0|acc |↑ |0.7851|± |0.0375| |
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| - jurisprudence | 0|none | 0|acc |↑ |0.7593|± |0.0413| |
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| - logical_fallacies | 0|none | 0|acc |↑ |0.7607|± |0.0335| |
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| - moral_disputes | 0|none | 0|acc |↑ |0.7197|± |0.0242| |
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| - moral_scenarios | 0|none | 0|acc |↑ |0.4045|± |0.0164| |
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| - philosophy | 0|none | 0|acc |↑ |0.7074|± |0.0258| |
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| - prehistory | 0|none | 0|acc |↑ |0.6975|± |0.0256| |
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| - professional_law | 0|none | 0|acc |↑ |0.4817|± |0.0128| |
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| - world_religions | 0|none | 0|acc |↑ |0.7953|± |0.0309| |
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| - other | 1|none | |acc |↑ |0.7100|± |0.0078| |
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| - business_ethics | 0|none | 0|acc |↑ |0.6700|± |0.0473| |
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| - clinical_knowledge | 0|none | 0|acc |↑ |0.7660|± |0.0261| |
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| - college_medicine | 0|none | 0|acc |↑ |0.6590|± |0.0361| |
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| - global_facts | 0|none | 0|acc |↑ |0.3600|± |0.0482| |
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| - human_aging | 0|none | 0|acc |↑ |0.6547|± |0.0319| |
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| - management | 0|none | 0|acc |↑ |0.8447|± |0.0359| |
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| - marketing | 0|none | 0|acc |↑ |0.8803|± |0.0213| |
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| - medical_genetics | 0|none | 0|acc |↑ |0.7100|± |0.0456| |
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| - miscellaneous | 0|none | 0|acc |↑ |0.8161|± |0.0139| |
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| - nutrition | 0|none | 0|acc |↑ |0.7124|± |0.0259| |
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| - professional_accounting | 0|none | 0|acc |↑ |0.4787|± |0.0298| |
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| - professional_medicine | 0|none | 0|acc |↑ |0.7279|± |0.0270| |
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| - virology | 0|none | 0|acc |↑ |0.5181|± |0.0389| |
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| - social sciences | 1|none | |acc |↑ |0.7312|± |0.0078| |
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| - econometrics | 0|none | 0|acc |↑ |0.4035|± |0.0462| |
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| - high_school_geography | 0|none | 0|acc |↑ |0.8232|± |0.0272| |
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| - high_school_government_and_politics| 0|none | 0|acc |↑ |0.8653|± |0.0246| |
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| - high_school_macroeconomics | 0|none | 0|acc |↑ |0.6128|± |0.0247| |
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| - high_school_microeconomics | 0|none | 0|acc |↑ |0.7227|± |0.0291| |
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| - high_school_psychology | 0|none | 0|acc |↑ |0.8422|± |0.0156| |
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| - human_sexuality | 0|none | 0|acc |↑ |0.7634|± |0.0373| |
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| - professional_psychology | 0|none | 0|acc |↑ |0.6585|± |0.0192| |
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| - public_relations | 0|none | 0|acc |↑ |0.6182|± |0.0465| |
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| - security_studies | 0|none | 0|acc |↑ |0.7306|± |0.0284| |
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| - sociology | 0|none | 0|acc |↑ |0.8358|± |0.0262| |
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| - us_foreign_policy | 0|none | 0|acc |↑ |0.8600|± |0.0349| |
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| - stem | 1|none | |acc |↑ |0.5623|± |0.0085| |
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| - abstract_algebra | 0|none | 0|acc |↑ |0.3800|± |0.0488| |
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| - anatomy | 0|none | 0|acc |↑ |0.6222|± |0.0419| |
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| - astronomy | 0|none | 0|acc |↑ |0.7039|± |0.0372| |
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| - college_biology | 0|none | 0|acc |↑ |0.7778|± |0.0348| |
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| - college_chemistry | 0|none | 0|acc |↑ |0.5400|± |0.0501| |
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| - college_computer_science | 0|none | 0|acc |↑ |0.5300|± |0.0502| |
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| - college_mathematics | 0|none | 0|acc |↑ |0.3200|± |0.0469| |
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| - college_physics | 0|none | 0|acc |↑ |0.4608|± |0.0496| |
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| - computer_security | 0|none | 0|acc |↑ |0.7800|± |0.0416| |
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| - conceptual_physics | 0|none | 0|acc |↑ |0.5617|± |0.0324| |
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| - electrical_engineering | 0|none | 0|acc |↑ |0.6138|± |0.0406| |
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| - elementary_mathematics | 0|none | 0|acc |↑ |0.4365|± |0.0255| |
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| - high_school_biology | 0|none | 0|acc |↑ |0.7839|± |0.0234| |
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| - high_school_chemistry | 0|none | 0|acc |↑ |0.5665|± |0.0349| |
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| - high_school_computer_science | 0|none | 0|acc |↑ |0.6600|± |0.0476| |
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| - high_school_mathematics | 0|none | 0|acc |↑ |0.4407|± |0.0303| |
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| - high_school_physics | 0|none | 0|acc |↑ |0.4371|± |0.0405| |
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| - high_school_statistics | 0|none | 0|acc |↑ |0.5602|± |0.0339| |
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| - machine_learning | 0|none | 0|acc |↑ |0.4643|± |0.0473| |
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|openbookqa | 1|none | 0|acc |↑ |0.3180|± |0.0208| |
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| | |none | 0|acc_norm |↑ |0.4140|± |0.0220| |
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|piqa | 1|none | 0|acc |↑ |0.7878|± |0.0095| |
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| | |none | 0|acc_norm |↑ |0.7971|± |0.0094| |
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|rte | 1|none | 0|acc |↑ |0.6751|± |0.0282| |
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|truthfulqa_mc1 | 2|none | 0|acc |↑ |0.3403|± |0.0166| |
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|winogrande | 1|none | 0|acc |↑ |0.7206|± |0.0126| |
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| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr| |
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|------------------|------:|------|------|------|---|-----:|---|-----:| |
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|mmlu | 1|none | |acc |↑ |0.6411|± |0.0038| |
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| - humanities | 1|none | |acc |↑ |0.5896|± |0.0068| |
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| - other | 1|none | |acc |↑ |0.7100|± |0.0078| |
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| - social sciences| 1|none | |acc |↑ |0.7312|± |0.0078| |
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| - stem | 1|none | |acc |↑ |0.5623|± |0.0085| |
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``` |
