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1!pip install -q -U transformers
2!pip install -q -U accelerate
3!pip install -q -U bitsandbytes
4
5from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
6model = AutoModelForCausalLM.from_pretrained("rhaymison/phi-3-portuguese-tom-cat-4k-instruct", device_map= {"": 0})
7tokenizer = AutoTokenizer.from_pretrained("rhaymison/phi-3-portuguese-tom-cat-4k-instruct")
8model.eval()
91
2from transformers import pipeline
3pipe = pipeline("text-generation",
4 model=model,
5 tokenizer=tokenizer,
6 do_sample=True,
7 max_new_tokens=512,
8 num_beams=2,
9 temperature=0.3,
10 top_k=50,
11 top_p=0.95,
12 early_stopping=True,
13 pad_token_id=tokenizer.eos_token_id,
14 )
15
16
17def format_template(question:str):
18 system_prompt = "Abaixo está uma instrução que descreve uma tarefa, juntamente com uma entrada que fornece mais contexto. Escreva uma resposta que complete adequadamente o pedido."
19 return f"""<s><|system|>
20 { system_prompt }
21 <|user|>
22 { question }
23 <|assistant|>
24 """
25
26question = format_template("E possivel ir de Carro dos Estados unidos ate o japão")
27pipe(question)1from transformers import BitsAndBytesConfig
2import torch
3nb_4bit_config = BitsAndBytesConfig(
4 load_in_4bit=True,
5 bnb_4bit_quant_type="nf4",
6 bnb_4bit_compute_dtype=torch.bfloat16,
7 bnb_4bit_use_double_quant=True
8)
9
10model = AutoModelForCausalLM.from_pretrained(
11 base_model,
12 quantization_config=bnb_config,
13 device_map={"": 0}
14)
15| Metric | Value |
|---|---|
| Average | 64.57 |
| ENEM Challenge (No Images) | 61.58 |
| BLUEX (No Images) | 50.63 |
| OAB Exams | 43.69 |
| Assin2 RTE | 91.54 |
| Assin2 STS | 75.27 |
| FaQuAD NLI | 47.46 |
| HateBR Binary | 83.01 |
| PT Hate Speech Binary | 70.19 |
| tweetSentBR | 57.78 |
