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--- |
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tags: |
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- fp8 |
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- vllm |
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--- |
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Created using AutoFP8: |
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```python |
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from datasets import load_dataset |
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from transformers import AutoTokenizer |
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from auto_fp8 import AutoFP8ForCausalLM, BaseQuantizeConfig |
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pretrained_model_dir = "meta-llama/Llama-2-70b-chat-hf" |
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quantized_model_dir = "Llama-2-70b-chat-hf-FP8" |
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tokenizer = AutoTokenizer.from_pretrained(pretrained_model_dir, use_fast=False) |
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tokenizer.pad_token = tokenizer.eos_token |
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# Load and tokenize all dataset samples for calibration of activation scales |
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ds = load_dataset("mgoin/ultrachat_2k", split="train_sft") |
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examples = [tokenizer.apply_chat_template(batch["messages"], tokenize=False) for batch in ds] |
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examples = tokenizer(examples, padding=True, truncation=True, return_tensors="pt", max_length=4096).to("cuda") |
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print(examples) |
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# Define quantization config with static activation scales |
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quantize_config = BaseQuantizeConfig( |
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quant_method="fp8", |
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activation_scheme="static", |
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ignore_patterns=["re:.*lm_head"], |
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) |
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# Load the model, quantize, and save checkpoint |
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model = AutoFP8ForCausalLM.from_pretrained(pretrained_model_dir, quantize_config) |
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model.quantize(examples) |
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model.save_quantized(quantized_model_dir) |
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``` |
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Evaluation: |
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``` |
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vllm (pretrained=meta-llama/Llama-2-70b-chat-hf,tensor_parallel_size=2,distributed_executor_backend=ray), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto |
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|Tasks|Version| Filter |n-shot| Metric | |Value | |Stderr| |
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|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:| |
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|gsm8k| 3|flexible-extract| 5|exact_match|↑ |0.5307|± |0.0137| |
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| | |strict-match | 5|exact_match|↑ |0.5064|± |0.0138| |
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vllm (pretrained=nm-testing/Llama-2-70b-chat-hf-FP8,tensor_parallel_size=2,distributed_executor_backend=ray), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto |
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|Tasks|Version| Filter |n-shot| Metric | |Value | |Stderr| |
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|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:| |
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|gsm8k| 3|flexible-extract| 5|exact_match|↑ |0.5625|± |0.0137| |
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| | |strict-match | 5|exact_match|↑ |0.5428|± |0.0137| |
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``` |
