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tsavage68_Summary_L3_1000steps_1e7rate_SFT2-GGUF
tensorblock/tsavage68_Summary_L3_1000steps_1e7rate_SFT2-GGUF
tsavage68_Summary_L3_1000steps_1e7rate_SFT2-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. The card lists the license as llama3.
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Repo size
61.5 GB
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Repo makeup
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.gguf3.2 GB · 100%
At a glance
- License
- llama3
- Access
- Public
- Created
- Apr 29, 2025
- Updated
- Jan 27, 2026
- SHA
- 560f5b25
Base models
Model card
From the Hugging Face model README
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tsavage68/Summary_L3_1000steps_1e7rate_SFT2 - GGUF
This repo contains GGUF format model files for tsavage68/Summary_L3_1000steps_1e7rate_SFT2.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Our projects
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Summary_L3_1000steps_1e7rate_SFT2-Q2_K.gguf | Q2_K | 3.179 GB | smallest, significant quality loss - not recommended for most purposes |
| Summary_L3_1000steps_1e7rate_SFT2-Q3_K_S.gguf | Q3_K_S | 3.664 GB | very small, high quality loss |
| Summary_L3_1000steps_1e7rate_SFT2-Q3_K_M.gguf | Q3_K_M | 4.019 GB | very small, high quality loss |
| Summary_L3_1000steps_1e7rate_SFT2-Q3_K_L.gguf | Q3_K_L | 4.322 GB | small, substantial quality loss |
| Summary_L3_1000steps_1e7rate_SFT2-Q4_0.gguf | Q4_0 | 4.661 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Summary_L3_1000steps_1e7rate_SFT2-Q4_K_S.gguf | Q4_K_S | 4.693 GB | small, greater quality loss |
| Summary_L3_1000steps_1e7rate_SFT2-Q4_K_M.gguf | Q4_K_M | 4.921 GB | medium, balanced quality - recommended |
| Summary_L3_1000steps_1e7rate_SFT2-Q5_0.gguf | Q5_0 | 5.599 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Summary_L3_1000steps_1e7rate_SFT2-Q5_K_S.gguf | Q5_K_S | 5.599 GB | large, low quality loss - recommended |
| Summary_L3_1000steps_1e7rate_SFT2-Q5_K_M.gguf | Q5_K_M | 5.733 GB | large, very low quality loss - recommended |
| Summary_L3_1000steps_1e7rate_SFT2-Q6_K.gguf | Q6_K | 6.596 GB | very large, extremely low quality loss |
| Summary_L3_1000steps_1e7rate_SFT2-Q8_0.gguf | Q8_0 | 8.541 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/tsavage68_Summary_L3_1000steps_1e7rate_SFT2-GGUF --include "Summary_L3_1000steps_1e7rate_SFT2-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/tsavage68_Summary_L3_1000steps_1e7rate_SFT2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- License
- llama3
- Created
- Apr 29, 2025
- Updated
- Jan 27, 2026