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tensorblock/klosax_pythia-160m-deduped-step92k-193bt-GGUF
klosax_pythia-160m-deduped-step92k-193bt-GGUF is a machine learning model from tensorblock. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf78.1 MB · 100%
From the Hugging Face model README
This repo contains GGUF format model files for klosax/pythia-160m-deduped-step92k-193bt.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| pythia-160m-deduped-step92k-193bt-Q2_K.gguf | Q2_K | 0.078 GB | smallest, significant quality loss - not recommended for most purposes |
| pythia-160m-deduped-step92k-193bt-Q3_K_S.gguf | Q3_K_S | 0.087 GB | very small, high quality loss |
| pythia-160m-deduped-step92k-193bt-Q3_K_M.gguf | Q3_K_M | 0.095 GB | very small, high quality loss |
| pythia-160m-deduped-step92k-193bt-Q3_K_L.gguf | Q3_K_L | 0.099 GB | small, substantial quality loss |
| pythia-160m-deduped-step92k-193bt-Q4_0.gguf | Q4_0 | 0.103 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| pythia-160m-deduped-step92k-193bt-Q4_K_S.gguf | Q4_K_S | 0.104 GB | small, greater quality loss |
| pythia-160m-deduped-step92k-193bt-Q4_K_M.gguf | Q4_K_M | 0.110 GB | medium, balanced quality - recommended |
| pythia-160m-deduped-step92k-193bt-Q5_0.gguf | Q5_0 | 0.119 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| pythia-160m-deduped-step92k-193bt-Q5_K_S.gguf | Q5_K_S | 0.119 GB | large, low quality loss - recommended |
| pythia-160m-deduped-step92k-193bt-Q5_K_M.gguf | Q5_K_M | 0.124 GB | large, very low quality loss - recommended |
| pythia-160m-deduped-step92k-193bt-Q6_K.gguf | Q6_K | 0.135 GB | very large, extremely low quality loss |
| pythia-160m-deduped-step92k-193bt-Q8_0.gguf | Q8_0 | 0.175 GB | very large, extremely low quality loss - not recommended |
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/klosax_pythia-160m-deduped-step92k-193bt-GGUF --include "pythia-160m-deduped-step92k-193bt-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/klosax_pythia-160m-deduped-step92k-193bt-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'