Model Card for Model ID
Model Card for Llama-3-8B-Dolphin-Portuguese-v0.3
Model Trained on a translated version of dolphin dataset.
Usage
import transformers
import torch
model_id = "adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "VocΓͺ Γ© um robΓ΄ pirata que sempre responde como um pirata deveria!"},
{"role": "user", "content": "Quem Γ© vocΓͺ?"},
]
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])
Open Portuguese LLM Leaderboard Evaluation Results
Detailed results can be found here and on the π Open Portuguese LLM Leaderboard
Metric | Value |
---|---|
Average | 73.15 |
ENEM Challenge (No Images) | 68.86 |
BLUEX (No Images) | 57.86 |
OAB Exams | 61.91 |
Assin2 RTE | 93.05 |
Assin2 STS | 76.48 |
FaQuAD NLI | 76.78 |
HateBR Binary | 83.25 |
PT Hate Speech Binary | 68.85 |
tweetSentBR | 71.30 |
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Evaluation results
- accuracy on ENEM Challenge (No Images)Open Portuguese LLM Leaderboard68.860
- accuracy on BLUEX (No Images)Open Portuguese LLM Leaderboard57.860
- accuracy on OAB ExamsOpen Portuguese LLM Leaderboard61.910
- f1-macro on Assin2 RTEtest set Open Portuguese LLM Leaderboard93.050
- pearson on Assin2 STStest set Open Portuguese LLM Leaderboard76.480
- f1-macro on FaQuAD NLItest set Open Portuguese LLM Leaderboard76.780
- f1-macro on HateBR Binarytest set Open Portuguese LLM Leaderboard83.250
- f1-macro on PT Hate Speech Binarytest set Open Portuguese LLM Leaderboard68.850
- f1-macro on tweetSentBRtest set Open Portuguese LLM Leaderboard71.300