Created
April 23, 2024 10:45
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from transformers import AutoTokenizer, AutoModelForCausalLM | |
import torch | |
from typing import Any | |
from core.actions import Action | |
class InferWithLlama3Instruct(Action): | |
def __init__( | |
self, | |
hf_token: str, | |
device: str, | |
actionname: str = None, | |
): | |
super().__init__(actionname) | |
self.hf_token = hf_token | |
self.model_id = "meta-llama/Meta-Llama-3-8B-Instruct" | |
self.tokenizer = AutoTokenizer.from_pretrained(self.model_id) | |
self.device = device | |
if self.device == "mps": | |
# mps devices don't support bfloat16 | |
torch_dtype = torch.float16 | |
else: | |
torch_dtype = torch.bfloat16 | |
self.model = AutoModelForCausalLM.from_pretrained( | |
self.model_id, | |
torch_dtype=torch_dtype, | |
device_map=self.device, | |
token=self.hf_token | |
) | |
def do(self, messages, *args:Any, **kwargs: Any): | |
input_ids = self.tokenizer.apply_chat_template( | |
messages, | |
add_generation_prompt=True, | |
return_tensors="pt" | |
).to(self.model.device) | |
terminators = [ | |
self.tokenizer.eos_token_id, | |
self.tokenizer.convert_tokens_to_ids("<|eot_id|>") | |
] | |
output_tensors = self.model.generate( | |
input_ids, | |
max_new_tokens=256, | |
eos_token_id=terminators, | |
do_sample=True, | |
temperature=0.6, | |
top_p=0.9, | |
) | |
top_output_tensors = output_tensors[0][input_ids.shape[-1]:] | |
out = self.tokenizer.decode(top_output_tensors, skip_special_tokens=True) | |
return out | |
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