Intel/orca_dpo_pairs
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How to use tensorblock/Orca-SOLAR-4x10.7b-GGUF with Transformers:
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("tensorblock/Orca-SOLAR-4x10.7b-GGUF", device_map="auto")How to use tensorblock/Orca-SOLAR-4x10.7b-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama cli -hf tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
docker model run hf.co/tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
How to use tensorblock/Orca-SOLAR-4x10.7b-GGUF with Ollama:
ollama run hf.co/tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
How to use tensorblock/Orca-SOLAR-4x10.7b-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
How to use tensorblock/Orca-SOLAR-4x10.7b-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/Orca-SOLAR-4x10.7b-GGUF:Q2_K
lemonade run user.Orca-SOLAR-4x10.7b-GGUF-Q2_K
lemonade list
This repo contains GGUF format model files for macadeliccc/Orca-SOLAR-4x10.7b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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### System:
{system_prompt}
### User:
{prompt}
### Assistant:
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Orca-SOLAR-4x10.7b-Q2_K.gguf | Q2_K | 13.189 GB | smallest, significant quality loss - not recommended for most purposes |
| Orca-SOLAR-4x10.7b-Q3_K_S.gguf | Q3_K_S | 15.568 GB | very small, high quality loss |
| Orca-SOLAR-4x10.7b-Q3_K_M.gguf | Q3_K_M | 17.288 GB | very small, high quality loss |
| Orca-SOLAR-4x10.7b-Q3_K_L.gguf | Q3_K_L | 18.734 GB | small, substantial quality loss |
| Orca-SOLAR-4x10.7b-Q4_0.gguf | Q4_0 | 20.345 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Orca-SOLAR-4x10.7b-Q4_K_S.gguf | Q4_K_S | 20.523 GB | small, greater quality loss |
| Orca-SOLAR-4x10.7b-Q4_K_M.gguf | Q4_K_M | 21.824 GB | medium, balanced quality - recommended |
| Orca-SOLAR-4x10.7b-Q5_0.gguf | Q5_0 | 24.840 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Orca-SOLAR-4x10.7b-Q5_K_S.gguf | Q5_K_S | 24.840 GB | large, low quality loss - recommended |
| Orca-SOLAR-4x10.7b-Q5_K_M.gguf | Q5_K_M | 25.603 GB | large, very low quality loss - recommended |
| Orca-SOLAR-4x10.7b-Q6_K.gguf | Q6_K | 29.617 GB | very large, extremely low quality loss |
| Orca-SOLAR-4x10.7b-Q8_0.gguf | Q8_0 | 38.360 GB | very large, extremely low quality loss - not recommended |
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/Orca-SOLAR-4x10.7b-GGUF --include "Orca-SOLAR-4x10.7b-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/Orca-SOLAR-4x10.7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
2-bit
Base model
macadeliccc/Orca-SOLAR-4x10.7b