gemma-portuguese-tom-cat-2b-it

Model description

updated: 2024-04-10 20:06

The gemma-portuguese-tom-cat-2b-it model is a portuguese model trained with the superset dataset with 250,000 instructions. The model is mainly focused on text generation and instruction. The model was not trained on math and code tasks. The model is generalist with focus on understand portuguese inferences. With this fine tuning for portuguese, you can adjust the model for a specific field.

How to Use

from transformers import AutoTokenizer, pipeline
import torch

model = "rhaymison/gemma-portuguese-tom-cat-2b-it"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device="cuda",
)

messages = [
   {
      "role": "system",
      "content": "Abaixo está uma instrução que descreve uma tarefa, juntamente com uma entrada que fornece mais contexto. Escreva uma resposta que complete adequadamente o pedido."
    },
    {"role": "user", "content": "Me conte sobre a ida do homem a Lua."},
]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(
    prompt,
    max_new_tokens=256,
    do_sample=True,
    temperature=0.2,
    top_k=50,
    top_p=0.95
)

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer2 = AutoTokenizer.from_pretrained("rhaymison/gemma-portuguese-tom-cat-2b-it")
model2 = AutoModelForCausalLM.from_pretrained("rhaymison/gemma-portuguese-tom-cat-2b-it", device_map={"":0})
tokenizer2.pad_token = tokenizer2.eos_token
tokenizer2.add_eos_token = True
tokenizer2.add_bos_token, tokenizer2.add_eos_token
tokenizer2.padding_side = "right"

def format_template( question:str):
    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."
    text = f"""<bos>system
    {system_prompt}<end_of_turn>
    <start_of_turn>user
    ###instrução: {question} <end_of_turn>
    <start_of_turn>model"""
    return text

question = format_template("Me conte sobre a ida do homem a Lua")

device = "cuda:0"

inputs = tokenizer2(text, return_tensors="pt").to(device)

outputs = model2.generate(**inputs, max_new_tokens=256, do_sample=False)

output = tokenizer2.decode(outputs[0], skip_special_tokens=True, skip_prompt=True)
print(output.replace("model"," "))

Comments

Any idea, help or report will always be welcome.

email: [email protected]

Open Portuguese LLM Leaderboard Evaluation Results

Detailed results can be found here and on the 🚀 Open Portuguese LLM Leaderboard

Metric	Value
Average	31.76
ENEM Challenge (No Images)	27.71
BLUEX (No Images)	29.07
OAB Exams	27.97
Assin2 RTE	46.84
Assin2 STS	14.06
FaQuAD NLI	29.39
HateBR Binary	46.59
PT Hate Speech Binary	45.36
tweetSentBR	18.86