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RichardErkhov/
rhaymison_-_gemma-portuguese-tom-cat-2b-it-gguf

Name: rhaymison_-_gemma-portuguese-tom-cat-2b-it-gguf
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gemma-portuguese-tom-cat-2b-it - GGUF

Model creator: https://huggingface.co/rhaymison/
Original model: https://huggingface.co/rhaymison/gemma-portuguese-tom-cat-2b-it/

Name	Quant method	Size
gemma-portuguese-tom-cat-2b-it.Q2_K.gguf	Q2_K	1.08GB
gemma-portuguese-tom-cat-2b-it.IQ3_XS.gguf	IQ3_XS	1.16GB
gemma-portuguese-tom-cat-2b-it.IQ3_S.gguf	IQ3_S	1.2GB
gemma-portuguese-tom-cat-2b-it.Q3_K_S.gguf	Q3_K_S	1.2GB
gemma-portuguese-tom-cat-2b-it.IQ3_M.gguf	IQ3_M	1.22GB
gemma-portuguese-tom-cat-2b-it.Q3_K.gguf	Q3_K	1.29GB
gemma-portuguese-tom-cat-2b-it.Q3_K_M.gguf	Q3_K_M	1.29GB
gemma-portuguese-tom-cat-2b-it.Q3_K_L.gguf	Q3_K_L	1.36GB
gemma-portuguese-tom-cat-2b-it.IQ4_XS.gguf	IQ4_XS	1.4GB
gemma-portuguese-tom-cat-2b-it.Q4_0.gguf	Q4_0	1.44GB
gemma-portuguese-tom-cat-2b-it.IQ4_NL.gguf	IQ4_NL	1.45GB
gemma-portuguese-tom-cat-2b-it.Q4_K_S.gguf	Q4_K_S	1.45GB
gemma-portuguese-tom-cat-2b-it.Q4_K.gguf	Q4_K	1.52GB
gemma-portuguese-tom-cat-2b-it.Q4_K_M.gguf	Q4_K_M	1.52GB
gemma-portuguese-tom-cat-2b-it.Q4_1.gguf	Q4_1	1.56GB
gemma-portuguese-tom-cat-2b-it.Q5_0.gguf	Q5_0	1.68GB
gemma-portuguese-tom-cat-2b-it.Q5_K_S.gguf	Q5_K_S	1.68GB
gemma-portuguese-tom-cat-2b-it.Q5_K.gguf	Q5_K	1.71GB
gemma-portuguese-tom-cat-2b-it.Q5_K_M.gguf	Q5_K_M	1.71GB
gemma-portuguese-tom-cat-2b-it.Q5_1.gguf	Q5_1	1.79GB
gemma-portuguese-tom-cat-2b-it.Q6_K.gguf	Q6_K	1.92GB
gemma-portuguese-tom-cat-2b-it.Q8_0.gguf	Q8_0	2.49GB

Original model description:

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"""<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: rhaymisoncristian@gmail.com

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

RichardErkhov/rhaymison_-_gemma-portuguese-tom-cat-2b-it-gguf

Original model description:

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

Model description

How to Use

Comments

Open Portuguese LLM Leaderboard Evaluation Results

RichardErkhov/
rhaymison_-_gemma-portuguese-tom-cat-2b-it-gguf