--- license: other license_name: yi-license license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE datasets: - ai2_arc - unalignment/spicy-3.1 - 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 base_model: jondurbin/bagel-dpo-34b-v0.2 tags: - TensorBlock - GGUF ---
TensorBlock

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## jondurbin/bagel-dpo-34b-v0.2 - GGUF This repo contains GGUF format model files for [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` [INST] <> {system_prompt} <> {prompt} [/INST] ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [bagel-dpo-34b-v0.2-Q2_K.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q2_K.gguf) | Q2_K | 11.944 GB | smallest, significant quality loss - not recommended for most purposes | | [bagel-dpo-34b-v0.2-Q3_K_S.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q3_K_S.gguf) | Q3_K_S | 13.933 GB | very small, high quality loss | | [bagel-dpo-34b-v0.2-Q3_K_M.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q3_K_M.gguf) | Q3_K_M | 15.511 GB | very small, high quality loss | | [bagel-dpo-34b-v0.2-Q3_K_L.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q3_K_L.gguf) | Q3_K_L | 16.894 GB | small, substantial quality loss | | [bagel-dpo-34b-v0.2-Q4_0.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q4_0.gguf) | Q4_0 | 18.130 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [bagel-dpo-34b-v0.2-Q4_K_S.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q4_K_S.gguf) | Q4_K_S | 18.253 GB | small, greater quality loss | | [bagel-dpo-34b-v0.2-Q4_K_M.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q4_K_M.gguf) | Q4_K_M | 19.240 GB | medium, balanced quality - recommended | | [bagel-dpo-34b-v0.2-Q5_0.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q5_0.gguf) | Q5_0 | 22.080 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [bagel-dpo-34b-v0.2-Q5_K_S.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q5_K_S.gguf) | Q5_K_S | 22.080 GB | large, low quality loss - recommended | | [bagel-dpo-34b-v0.2-Q5_K_M.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q5_K_M.gguf) | Q5_K_M | 22.651 GB | large, very low quality loss - recommended | | [bagel-dpo-34b-v0.2-Q6_K.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q6_K.gguf) | Q6_K | 26.276 GB | very large, extremely low quality loss | | [bagel-dpo-34b-v0.2-Q8_0.gguf](https://huggingface.co/tensorblock/bagel-dpo-34b-v0.2-GGUF/blob/main/bagel-dpo-34b-v0.2-Q8_0.gguf) | Q8_0 | 34.033 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/bagel-dpo-34b-v0.2-GGUF --include "bagel-dpo-34b-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: ```shell huggingface-cli download tensorblock/bagel-dpo-34b-v0.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```