metadata
library_name: transformers
tags:
- not-for-all-audiences
- TensorBlock
- GGUF
base_model: Darkknight535/Moonlight-L3-15B-v2-64k
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
Darkknight535/Moonlight-L3-15B-v2-64k - GGUF
This repo contains GGUF format model files for Darkknight535/Moonlight-L3-15B-v2-64k.
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 |
|---|---|---|---|
| Moonlight-L3-15B-v2-64k-Q2_K.gguf | Q2_K | 5.352 GB | smallest, significant quality loss - not recommended for most purposes |
| Moonlight-L3-15B-v2-64k-Q3_K_S.gguf | Q3_K_S | 6.207 GB | very small, high quality loss |
| Moonlight-L3-15B-v2-64k-Q3_K_M.gguf | Q3_K_M | 6.866 GB | very small, high quality loss |
| Moonlight-L3-15B-v2-64k-Q3_K_L.gguf | Q3_K_L | 7.431 GB | small, substantial quality loss |
| Moonlight-L3-15B-v2-64k-Q4_0.gguf | Q4_0 | 7.998 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Moonlight-L3-15B-v2-64k-Q4_K_S.gguf | Q4_K_S | 8.055 GB | small, greater quality loss |
| Moonlight-L3-15B-v2-64k-Q4_K_M.gguf | Q4_K_M | 8.482 GB | medium, balanced quality - recommended |
| Moonlight-L3-15B-v2-64k-Q5_0.gguf | Q5_0 | 9.684 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Moonlight-L3-15B-v2-64k-Q5_K_S.gguf | Q5_K_S | 9.684 GB | large, low quality loss - recommended |
| Moonlight-L3-15B-v2-64k-Q5_K_M.gguf | Q5_K_M | 9.934 GB | large, very low quality loss - recommended |
| Moonlight-L3-15B-v2-64k-Q6_K.gguf | Q6_K | 11.476 GB | very large, extremely low quality loss |
| Moonlight-L3-15B-v2-64k-Q8_0.gguf | Q8_0 | 14.861 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/Moonlight-L3-15B-v2-64k-GGUF --include "Moonlight-L3-15B-v2-64k-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/Moonlight-L3-15B-v2-64k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'