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swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA - GGUF
This repo contains GGUF format model files for swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q2_K.gguf | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_S.gguf | Q3_K_S | 3.413 GB | very small, high quality loss |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_M.gguf | Q3_K_M | 3.743 GB | very small, high quality loss |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_L.gguf | Q3_K_L | 4.025 GB | small, substantial quality loss |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_0.gguf | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_K_S.gguf | Q4_K_S | 4.370 GB | small, greater quality loss |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_K_M.gguf | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_0.gguf | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_K_S.gguf | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_K_M.gguf | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q6_K.gguf | Q6_K | 6.143 GB | very large, extremely low quality loss |
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q8_0.gguf | Q8_0 | 7.954 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/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF --include "LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-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/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF
Base model
meta-llama/Meta-Llama-3-8B-InstructDatasets used to train tensorblock/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard74.570
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard92.750
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.850
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard75.930
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.000
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard58.610