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.gitattributes CHANGED
@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
@@ -0,0 +1,329 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ - TucanoBR/GigaVerbo
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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: A floresta da Amazônia é conhecida por sua
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+ example_title: Exemplo
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+ - text: Uma das coisas que Portugal, Angola, Brasil e Moçambique tem em comum é o
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+ example_title: Exemplo
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+ - text: O Carnaval do Rio de Janeiro é
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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: 960000
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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
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+ model-index:
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+ - name: Tucano-1b1
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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: 58.24
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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: 34.7
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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: 21.41
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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: 23.37
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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: 25.97
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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: 60.82
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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: 24.63
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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: 29.0
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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: 41.19
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+ name: f1-macro
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+ source:
197
+ 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: 32.18
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+ name: f1-macro
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+ source:
213
+ 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: 30.43
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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: 42.84
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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
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+ type: truthfulqa_pt
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+ args:
252
+ num_few_shot: 0
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+ metrics:
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+ - type: mc2
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+ value: 41.59
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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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+ ---
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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 - GGUF
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+
275
+ This repo contains GGUF format model files for [TucanoBR/Tucano-1b1](https://huggingface.co/TucanoBR/Tucano-1b1).
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+
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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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+
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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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+
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+ ## Prompt template
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+
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+ ```
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+
289
+ ```
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+
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+ ## Model file specification
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+
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+ | Filename | Quant type | File Size | Description |
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+ | -------- | ---------- | --------- | ----------- |
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+ | [Tucano-1b1-Q2_K.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q2_K.gguf) | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes |
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+ | [Tucano-1b1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q3_K_S.gguf) | Q3_K_S | 0.499 GB | very small, high quality loss |
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+ | [Tucano-1b1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q3_K_M.gguf) | Q3_K_M | 0.548 GB | very small, high quality loss |
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+ | [Tucano-1b1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q3_K_L.gguf) | Q3_K_L | 0.592 GB | small, substantial quality loss |
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+ | [Tucano-1b1-Q4_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-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-Q4_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q4_K_S.gguf) | Q4_K_S | 0.640 GB | small, greater quality loss |
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+ | [Tucano-1b1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q4_K_M.gguf) | Q4_K_M | 0.668 GB | medium, balanced quality - recommended |
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+ | [Tucano-1b1-Q5_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q5_0.gguf) | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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+ | [Tucano-1b1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q5_K_S.gguf) | Q5_K_S | 0.766 GB | large, low quality loss - recommended |
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+ | [Tucano-1b1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q5_K_M.gguf) | Q5_K_M | 0.782 GB | large, very low quality loss - recommended |
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+ | [Tucano-1b1-Q6_K.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q6_K.gguf) | Q6_K | 0.903 GB | very large, extremely low quality loss |
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+ | [Tucano-1b1-Q8_0.gguf](https://huggingface.co/tensorblock/Tucano-1b1-GGUF/blob/main/Tucano-1b1-Q8_0.gguf) | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended |
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+
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+
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+ ## Downloading instruction
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+
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+ ### Command line
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+
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+ Firstly, install Huggingface Client
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+
315
+ ```shell
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+ pip install -U "huggingface_hub[cli]"
317
+ ```
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+
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+ Then, downoad the individual model file the a local directory
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+
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+ ```shell
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+ huggingface-cli download tensorblock/Tucano-1b1-GGUF --include "Tucano-1b1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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+ ```
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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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+
327
+ ```shell
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+ huggingface-cli download tensorblock/Tucano-1b1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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+ ```
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