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TucanoBR/Tucano-1b1-Instruct - GGUF
This repo contains GGUF format model files for TucanoBR/Tucano-1b1-Instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
<instruction>{prompt}</instruction>
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
Tucano-1b1-Instruct-Q2_K.gguf | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes |
Tucano-1b1-Instruct-Q3_K_S.gguf | Q3_K_S | 0.499 GB | very small, high quality loss |
Tucano-1b1-Instruct-Q3_K_M.gguf | Q3_K_M | 0.548 GB | very small, high quality loss |
Tucano-1b1-Instruct-Q3_K_L.gguf | Q3_K_L | 0.592 GB | small, substantial quality loss |
Tucano-1b1-Instruct-Q4_0.gguf | Q4_0 | 0.637 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Tucano-1b1-Instruct-Q4_K_S.gguf | Q4_K_S | 0.640 GB | small, greater quality loss |
Tucano-1b1-Instruct-Q4_K_M.gguf | Q4_K_M | 0.668 GB | medium, balanced quality - recommended |
Tucano-1b1-Instruct-Q5_0.gguf | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Tucano-1b1-Instruct-Q5_K_S.gguf | Q5_K_S | 0.766 GB | large, low quality loss - recommended |
Tucano-1b1-Instruct-Q5_K_M.gguf | Q5_K_M | 0.782 GB | large, very low quality loss - recommended |
Tucano-1b1-Instruct-Q6_K.gguf | Q6_K | 0.903 GB | very large, extremely low quality loss |
Tucano-1b1-Instruct-Q8_0.gguf | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/Tucano-1b1-Instruct-GGUF --include "Tucano-1b1-Instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf
), you can try:
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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Model tree for tensorblock/Tucano-1b1-Instruct-GGUF
Datasets used to train tensorblock/Tucano-1b1-Instruct-GGUF
Evaluation results
- accuracy on CALAME-PTContext-Aware LAnguage Modeling Evaluation for Portuguese56.550
- accuracy on LAMBADA-PTLAMBADA-PT35.530
- accuracy on ENEM Challenge (No Images)Open Portuguese LLM Leaderboard21.060
- accuracy on BLUEX (No Images)Open Portuguese LLM Leaderboard26.010
- accuracy on OAB ExamsOpen Portuguese LLM Leaderboard26.470
- f1-macro on Assin2 RTEtest set Open Portuguese LLM Leaderboard67.780
- pearson on Assin2 STStest set Open Portuguese LLM Leaderboard8.880
- f1-macro on FaQuAD NLItest set Open Portuguese LLM Leaderboard43.970
- f1-macro on HateBR Binarytest set Open Portuguese LLM Leaderboard31.280
- f1-macro on PT Hate Speech Binarytest set Open Portuguese LLM Leaderboard41.230