metadata
license: mit
datasets:
- Open-Orca/OpenOrca
- conceptofmind/cot_submix_original
- conceptofmind/t0_submix_original
- conceptofmind/niv2_submix_original
- conceptofmind/flan2021_submix_original
- ehartford/dolphin
language:
- en
tags:
- merge
- slerp
- TensorBlock
- GGUF
inference: false
metrics:
- accuracy
- bleu
base_model: NewstaR/7B-Orfini
NewstaR/7B-Orfini - GGUF
This repo contains GGUF format model files for NewstaR/7B-Orfini.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Our projects
| Awesome MCP Servers | TensorBlock Studio |
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| 👀 See what we built 👀 | 👀 See what we built 👀 |
Prompt template
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| 7B-Orfini-Q2_K.gguf | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
| 7B-Orfini-Q3_K_S.gguf | Q3_K_S | 2.948 GB | very small, high quality loss |
| 7B-Orfini-Q3_K_M.gguf | Q3_K_M | 3.298 GB | very small, high quality loss |
| 7B-Orfini-Q3_K_L.gguf | Q3_K_L | 3.597 GB | small, substantial quality loss |
| 7B-Orfini-Q4_0.gguf | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| 7B-Orfini-Q4_K_S.gguf | Q4_K_S | 3.857 GB | small, greater quality loss |
| 7B-Orfini-Q4_K_M.gguf | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
| 7B-Orfini-Q5_0.gguf | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| 7B-Orfini-Q5_K_S.gguf | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
| 7B-Orfini-Q5_K_M.gguf | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
| 7B-Orfini-Q6_K.gguf | Q6_K | 5.529 GB | very large, extremely low quality loss |
| 7B-Orfini-Q8_0.gguf | Q8_0 | 7.161 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/NewstaR_7B-Orfini-GGUF --include "7B-Orfini-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/NewstaR_7B-Orfini-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'