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--- |
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language: |
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- pt |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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- TensorBlock |
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- GGUF |
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datasets: |
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- nicholasKluge/instruct-aira-dataset-v3 |
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- cnmoro/GPT4-500k-Augmented-PTBR-Clean |
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- rhaymison/orca-math-portuguese-64k |
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- nicholasKluge/reward-aira-dataset |
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metrics: |
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- perplexity |
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pipeline_tag: text-generation |
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widget: |
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- text: <instruction>Cite algumas bandas de rock brasileiras famosas.</instruction> |
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example_title: Exemplo |
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- text: <instruction>Invente uma história sobre um encanador com poderes mágicos.</instruction> |
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example_title: Exemplo |
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- text: <instruction>Qual cidade é a capital do estado do Rio Grande do Sul?</instruction> |
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example_title: Exemplo |
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- text: <instruction>Diga o nome de uma maravilha culinária característica da cosinha |
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Portuguesa?</instruction> |
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example_title: Exemplo |
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inference: |
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parameters: |
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repetition_penalty: 1.2 |
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temperature: 0.2 |
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top_k: 20 |
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top_p: 0.2 |
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max_new_tokens: 150 |
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co2_eq_emissions: |
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emissions: 21890 |
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source: CodeCarbon |
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training_type: pre-training |
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geographical_location: Germany |
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hardware_used: NVIDIA A100-SXM4-80GB |
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base_model: TucanoBR/Tucano-1b1-Instruct |
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model-index: |
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- name: Tucano-1b1-Instruct |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: CALAME-PT |
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type: NOVA-vision-language/calame-pt |
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split: all |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc |
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value: 56.55 |
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name: accuracy |
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source: |
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url: https://huggingface.co/datasets/NOVA-vision-language/calame-pt |
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name: Context-Aware LAnguage Modeling Evaluation for Portuguese |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: LAMBADA-PT |
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type: TucanoBR/lambada-pt |
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split: train |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc |
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value: 35.53 |
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name: accuracy |
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source: |
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url: https://huggingface.co/datasets/TucanoBR/lambada-pt |
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name: LAMBADA-PT |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: ENEM Challenge (No Images) |
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type: eduagarcia/enem_challenge |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 21.06 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BLUEX (No Images) |
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type: eduagarcia-temp/BLUEX_without_images |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 26.01 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: OAB Exams |
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type: eduagarcia/oab_exams |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 26.47 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Assin2 RTE |
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type: assin2 |
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split: test |
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args: |
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num_few_shot: 15 |
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metrics: |
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- type: f1_macro |
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value: 67.78 |
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name: f1-macro |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Assin2 STS |
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type: eduagarcia/portuguese_benchmark |
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split: test |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: pearson |
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value: 8.88 |
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name: pearson |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: FaQuAD NLI |
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type: ruanchaves/faquad-nli |
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split: test |
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args: |
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num_few_shot: 15 |
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metrics: |
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- type: f1_macro |
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value: 43.97 |
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name: f1-macro |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HateBR Binary |
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type: ruanchaves/hatebr |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: f1_macro |
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value: 31.28 |
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name: f1-macro |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: PT Hate Speech Binary |
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type: hate_speech_portuguese |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: f1_macro |
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value: 41.23 |
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name: f1-macro |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: tweetSentBR |
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type: eduagarcia-temp/tweetsentbr |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: f1_macro |
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value: 22.03 |
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name: f1-macro |
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source: |
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard |
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name: Open Portuguese LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: ARC-Challenge (PT) |
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type: arc_pt |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 30.77 |
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name: normalized accuracy |
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source: |
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url: https://github.com/nlp-uoregon/mlmm-evaluation |
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name: Evaluation Framework for Multilingual Large Language Models |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (PT) |
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type: hellaswag_pt |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 43.5 |
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name: normalized accuracy |
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source: |
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url: https://github.com/nlp-uoregon/mlmm-evaluation |
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name: Evaluation Framework for Multilingual Large Language Models |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (PT) |
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type: truthfulqa_pt |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 41.14 |
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name: bleurt |
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source: |
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url: https://github.com/nlp-uoregon/mlmm-evaluation |
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name: Evaluation Framework for Multilingual Large Language Models |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Alpaca-Eval (PT) |
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type: alpaca_eval_pt |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: lc_winrate |
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value: 8.8 |
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name: length controlled winrate |
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source: |
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url: https://github.com/tatsu-lab/alpaca_eval |
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name: AlpacaEval |
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--- |
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|
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<div style="width: auto; margin-left: auto; margin-right: auto"> |
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<div style="display: flex; justify-content: space-between; width: 100%;"> |
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<div style="display: flex; flex-direction: column; align-items: flex-start;"> |
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<p style="margin-top: 0.5em; margin-bottom: 0em;"> |
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a> |
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</p> |
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</div> |
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</div> |
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|
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## TucanoBR/Tucano-1b1-Instruct - GGUF |
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This repo contains GGUF format model files for [TucanoBR/Tucano-1b1-Instruct](https://huggingface.co/TucanoBR/Tucano-1b1-Instruct). |
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
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<div style="text-align: left; margin: 20px 0;"> |
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;"> |
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Run them on the TensorBlock client using your local machine ↗ |
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</a> |
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</div> |
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## Prompt template |
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``` |
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<instruction>{prompt}</instruction> |
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``` |
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## Model file specification |
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| Filename | Quant type | File Size | Description | |
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| -------- | ---------- | --------- | ----------- | |
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| [Tucano-1b1-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q2_K.gguf) | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [Tucano-1b1-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q3_K_S.gguf) | Q3_K_S | 0.499 GB | very small, high quality loss | |
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| [Tucano-1b1-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q3_K_M.gguf) | Q3_K_M | 0.548 GB | very small, high quality loss | |
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| [Tucano-1b1-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q3_K_L.gguf) | Q3_K_L | 0.592 GB | small, substantial quality loss | |
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| [Tucano-1b1-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q4_0.gguf) | Q4_0 | 0.637 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [Tucano-1b1-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q4_K_S.gguf) | Q4_K_S | 0.640 GB | small, greater quality loss | |
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| [Tucano-1b1-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q4_K_M.gguf) | Q4_K_M | 0.668 GB | medium, balanced quality - recommended | |
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| [Tucano-1b1-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q5_0.gguf) | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [Tucano-1b1-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q5_K_S.gguf) | Q5_K_S | 0.766 GB | large, low quality loss - recommended | |
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| [Tucano-1b1-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q5_K_M.gguf) | Q5_K_M | 0.782 GB | large, very low quality loss - recommended | |
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| [Tucano-1b1-Instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q6_K.gguf) | Q6_K | 0.903 GB | very large, extremely low quality loss | |
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| [Tucano-1b1-Instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-Instruct-GGUF/blob/main/Tucano-1b1-Instruct-Q8_0.gguf) | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended | |
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## Downloading instruction |
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### Command line |
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Firstly, install Huggingface Client |
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```shell |
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pip install -U "huggingface_hub[cli]" |
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``` |
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Then, downoad the individual model file the a local directory |
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```shell |
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huggingface-cli download tensorblock/Tucano-1b1-Instruct-GGUF --include "Tucano-1b1-Instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
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``` |
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
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```shell |
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huggingface-cli download tensorblock/Tucano-1b1-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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