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tensorblock/tsum_base-GGUF
tsum_base-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. It is set up for transformers.
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Downloads Β· 30 days
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.gguf3.2 GB Β· 100%
From the Hugging Face model README
This repo contains GGUF format model files for rndteam41/tsum_base.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
<|begin_of_text|><|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| tsum_base-Q2_K.gguf | Q2_K | 3.179 GB | smallest, significant quality loss - not recommended for most purposes |
| tsum_base-Q3_K_S.gguf | Q3_K_S | 3.665 GB | very small, high quality loss |
| tsum_base-Q3_K_M.gguf | Q3_K_M | 4.019 GB | very small, high quality loss |
| tsum_base-Q3_K_L.gguf | Q3_K_L | 4.322 GB | small, substantial quality loss |
| tsum_base-Q4_0.gguf | Q4_0 | 4.661 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| tsum_base-Q4_K_S.gguf | Q4_K_S | 4.693 GB | small, greater quality loss |
| tsum_base-Q4_K_M.gguf | Q4_K_M | 4.921 GB | medium, balanced quality - recommended |
| tsum_base-Q5_0.gguf | Q5_0 | 5.599 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| tsum_base-Q5_K_S.gguf | Q5_K_S | 5.599 GB | large, low quality loss - recommended |
| tsum_base-Q5_K_M.gguf | Q5_K_M | 5.733 GB | large, very low quality loss - recommended |
| tsum_base-Q6_K.gguf | Q6_K | 6.596 GB | very large, extremely low quality loss |
| tsum_base-Q8_0.gguf | Q8_0 | 8.541 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/tsum_base-GGUF --include "tsum_base-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/tsum_base-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'