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1import torch
2from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, GemmaTokenizer
3
4model_id = "alibidaran/Gemma2_Farsi"
5bnb_config = BitsAndBytesConfig(
6 load_in_4bit=True,
7 bnb_4bit_quant_type="nf4",
8 bnb_4bit_compute_dtype=torch.bfloat16
9)
10
11
12tokenizer = AutoTokenizer.from_pretrained(model_id, token=os.environ['HF_TOKEN'])
13model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device_map={"":0}, token=os.environ['HF_TOKEN'])
14prompt = "چند روش برای کاهش چربی بدن ارائه نمایید؟"
15text = f"<s> ###Human: {prompt} ###Asistant: "
16
17inputs=tokenizer(text,return_tensors='pt').to('cuda')
18with torch.no_grad():
19 outputs=model.generate(**inputs,max_new_tokens=400,do_sample=True,top_p=0.99,top_k=10,temperature=0.7)
20print(tokenizer.decode(outputs[0], skip_special_tokens=True))
21