metadata
license: cc-by-nc-4.0
datasets:
- pankajmathur/orca_mini_v1_dataset
- openai/summarize_from_feedback
- PygmalionAI/PIPPA
- chargoddard/rpguild
- lemonilia/LimaRP
- PKU-Alignment/PKU-SafeRLHF
- Intel/orca_dpo_pairs
- allenai/ultrafeedback_binarized_cleaned
base_model: chargoddard/servile-harpsichord-cdpo
tags:
- TensorBlock
- GGUF
chargoddard/servile-harpsichord-cdpo - GGUF
This repo contains GGUF format model files for chargoddard/servile-harpsichord-cdpo.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| servile-harpsichord-cdpo-Q2_K.gguf | Q2_K | 2.719 GB | smallest, significant quality loss - not recommended for most purposes |
| servile-harpsichord-cdpo-Q3_K_S.gguf | Q3_K_S | 3.165 GB | very small, high quality loss |
| servile-harpsichord-cdpo-Q3_K_M.gguf | Q3_K_M | 3.519 GB | very small, high quality loss |
| servile-harpsichord-cdpo-Q3_K_L.gguf | Q3_K_L | 3.822 GB | small, substantial quality loss |
| servile-harpsichord-cdpo-Q4_0.gguf | Q4_0 | 4.109 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| servile-harpsichord-cdpo-Q4_K_S.gguf | Q4_K_S | 4.140 GB | small, greater quality loss |
| servile-harpsichord-cdpo-Q4_K_M.gguf | Q4_K_M | 4.368 GB | medium, balanced quality - recommended |
| servile-harpsichord-cdpo-Q5_0.gguf | Q5_0 | 4.998 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| servile-harpsichord-cdpo-Q5_K_S.gguf | Q5_K_S | 4.998 GB | large, low quality loss - recommended |
| servile-harpsichord-cdpo-Q5_K_M.gguf | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
| servile-harpsichord-cdpo-Q6_K.gguf | Q6_K | 5.942 GB | very large, extremely low quality loss |
| servile-harpsichord-cdpo-Q8_0.gguf | Q8_0 | 7.696 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/servile-harpsichord-cdpo-GGUF --include "servile-harpsichord-cdpo-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/servile-harpsichord-cdpo-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'