Instructions to use mradermacher/BigWeave-v26-95b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/BigWeave-v26-95b-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/BigWeave-v26-95b-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/BigWeave-v26-95b-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/BigWeave-v26-95b-GGUF:Q2_K
Use Docker
docker model run hf.co/mradermacher/BigWeave-v26-95b-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use mradermacher/BigWeave-v26-95b-GGUF with Ollama:
ollama run hf.co/mradermacher/BigWeave-v26-95b-GGUF:Q2_K
- Unsloth Studio
How to use mradermacher/BigWeave-v26-95b-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/BigWeave-v26-95b-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/BigWeave-v26-95b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/BigWeave-v26-95b-GGUF to start chatting
- Docker Model Runner
How to use mradermacher/BigWeave-v26-95b-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/BigWeave-v26-95b-GGUF:Q2_K
- Lemonade
How to use mradermacher/BigWeave-v26-95b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/BigWeave-v26-95b-GGUF:Q2_K
Run and chat with the model
lemonade run user.BigWeave-v26-95b-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
auto-patch README.md
Browse files
README.md
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@@ -37,6 +37,7 @@ more details, including on how to concatenate multi-part files.
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| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_S.gguf) | Q3_K_S | 40.9 | |
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| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_M.gguf) | Q3_K_M | 45.6 | lower quality |
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| 39 |
| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_L.gguf) | Q3_K_L | 49.7 | |
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| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_S.gguf.part2of2) | Q4_K_S | 53.8 | fast, recommended |
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| 41 |
| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_M.gguf.part2of2) | Q4_K_M | 56.8 | fast, recommended |
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| 42 |
| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q5_K_S.gguf.part2of2) | Q5_K_S | 65.2 | |
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| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_S.gguf) | Q3_K_S | 40.9 | |
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| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_M.gguf) | Q3_K_M | 45.6 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q3_K_L.gguf) | Q3_K_L | 49.7 | |
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| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.IQ4_XS.gguf.part2of2) | IQ4_XS | 51.1 | |
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| 41 |
| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_S.gguf.part2of2) | Q4_K_S | 53.8 | fast, recommended |
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| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q4_K_M.gguf.part2of2) | Q4_K_M | 56.8 | fast, recommended |
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| 43 |
| [PART 1](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/BigWeave-v26-95b-GGUF/resolve/main/BigWeave-v26-95b.Q5_K_S.gguf.part2of2) | Q5_K_S | 65.2 | |
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