--- language: - pt license: apache-2.0 library_name: transformers tags: - portuguese - brasil - gemma - portugues - instrucao base_model: google/gemma-2b-it datasets: - rhaymison/superset pipeline_tag: text-generation model-index: - name: gemma-portuguese-tom-cat-2b-it results: - task: type: text-generation name: Text Generation dataset: name: ENEM Challenge (No Images) type: eduagarcia/enem_challenge split: train args: num_few_shot: 3 metrics: - type: acc value: 27.71 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BLUEX (No Images) type: eduagarcia-temp/BLUEX_without_images split: train args: num_few_shot: 3 metrics: - type: acc value: 29.07 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: OAB Exams type: eduagarcia/oab_exams split: train args: num_few_shot: 3 metrics: - type: acc value: 27.97 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 RTE type: assin2 split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 46.84 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 STS type: eduagarcia/portuguese_benchmark split: test args: num_few_shot: 15 metrics: - type: pearson value: 14.06 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: FaQuAD NLI type: ruanchaves/faquad-nli split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 29.39 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HateBR Binary type: ruanchaves/hatebr split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 46.59 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: PT Hate Speech Binary type: hate_speech_portuguese split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 45.36 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: tweetSentBR type: eduagarcia/tweetsentbr_fewshot split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 18.86 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard --- # 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 ```python 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 ) ``` ```python 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" ``` ```python 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"""system {system_prompt} user ###instrução: {question} 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: rhaymisoncristian@gmail.com # Open Portuguese LLM Leaderboard Evaluation Results Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/rhaymison/gemma-portuguese-tom-cat-2b-it) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_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|