metadata
license: apache-2.0
datasets:
- ai2_arc
- jondurbin/airoboros-3.2
- codeparrot/apps
- facebook/belebele
- boolq
- jondurbin/cinematika-v0.1
- drop
- lmsys/lmsys-chat-1m
- TIGER-Lab/MathInstruct
- cais/mmlu
- Muennighoff/natural-instructions
- openbookqa
- piqa
- Vezora/Tested-22k-Python-Alpaca
- cakiki/rosetta-code
- Open-Orca/SlimOrca
- spider
- squad_v2
- migtissera/Synthia-v1.3
- datasets/winogrande
- nvidia/HelpSteer
- Intel/orca_dpo_pairs
- unalignment/toxic-dpo-v0.1
- jondurbin/truthy-dpo-v0.1
- allenai/ultrafeedback_binarized_cleaned
- Squish42/bluemoon-fandom-1-1-rp-cleaned
- LDJnr/Capybara
- JULIELab/EmoBank
- kingbri/PIPPA-shareGPT
tags:
- TensorBlock
- GGUF
base_model: jondurbin/bagel-8x7b-v0.2
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
jondurbin/bagel-8x7b-v0.2 - GGUF
This repo contains GGUF format model files for jondurbin/bagel-8x7b-v0.2.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
[INST] <<SYS>>
{system_prompt}
<</SYS>>
{prompt} [/INST]
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| bagel-8x7b-v0.2-Q2_K.gguf | Q2_K | 17.311 GB | smallest, significant quality loss - not recommended for most purposes |
| bagel-8x7b-v0.2-Q3_K_S.gguf | Q3_K_S | 20.433 GB | very small, high quality loss |
| bagel-8x7b-v0.2-Q3_K_M.gguf | Q3_K_M | 22.546 GB | very small, high quality loss |
| bagel-8x7b-v0.2-Q3_K_L.gguf | Q3_K_L | 24.170 GB | small, substantial quality loss |
| bagel-8x7b-v0.2-Q4_0.gguf | Q4_0 | 26.444 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| bagel-8x7b-v0.2-Q4_K_S.gguf | Q4_K_S | 26.746 GB | small, greater quality loss |
| bagel-8x7b-v0.2-Q4_K_M.gguf | Q4_K_M | 28.448 GB | medium, balanced quality - recommended |
| bagel-8x7b-v0.2-Q5_0.gguf | Q5_0 | 32.231 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| bagel-8x7b-v0.2-Q5_K_S.gguf | Q5_K_S | 32.231 GB | large, low quality loss - recommended |
| bagel-8x7b-v0.2-Q5_K_M.gguf | Q5_K_M | 33.230 GB | large, very low quality loss - recommended |
| bagel-8x7b-v0.2-Q6_K.gguf | Q6_K | 38.381 GB | very large, extremely low quality loss |
| bagel-8x7b-v0.2-Q8_0.gguf | Q8_0 | 49.626 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/bagel-8x7b-v0.2-GGUF --include "bagel-8x7b-v0.2-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/bagel-8x7b-v0.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'