Instructions to use tensorblock/ConfigurableBeagle-11B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/ConfigurableBeagle-11B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/ConfigurableBeagle-11B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/ConfigurableBeagle-11B-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 tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/ConfigurableBeagle-11B-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 tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/ConfigurableBeagle-11B-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 tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/ConfigurableBeagle-11B-GGUF with Ollama:
ollama run hf.co/tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/ConfigurableBeagle-11B-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 tensorblock/ConfigurableBeagle-11B-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 tensorblock/ConfigurableBeagle-11B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tensorblock/ConfigurableBeagle-11B-GGUF to start chatting
- Docker Model Runner
How to use tensorblock/ConfigurableBeagle-11B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
- Lemonade
How to use tensorblock/ConfigurableBeagle-11B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/ConfigurableBeagle-11B-GGUF:Q2_K
Run and chat with the model
lemonade run user.ConfigurableBeagle-11B-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Update README.md
Browse files
README.md
CHANGED
|
@@ -221,8 +221,16 @@ This repo contains GGUF format model files for [vicgalle/ConfigurableBeagle-11B]
|
|
| 221 |
|
| 222 |
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).
|
| 223 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 224 |
## Prompt template
|
| 225 |
|
|
|
|
| 226 |
```
|
| 227 |
### System:
|
| 228 |
{system_prompt}
|
|
@@ -237,18 +245,18 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
|
|
| 237 |
|
| 238 |
| Filename | Quant type | File Size | Description |
|
| 239 |
| -------- | ---------- | --------- | ----------- |
|
| 240 |
-
| [ConfigurableBeagle-11B-Q2_K.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 241 |
-
| [ConfigurableBeagle-11B-Q3_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 242 |
-
| [ConfigurableBeagle-11B-Q3_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 243 |
-
| [ConfigurableBeagle-11B-Q3_K_L.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 244 |
-
| [ConfigurableBeagle-11B-Q4_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 245 |
-
| [ConfigurableBeagle-11B-Q4_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 246 |
-
| [ConfigurableBeagle-11B-Q4_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 247 |
-
| [ConfigurableBeagle-11B-Q5_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 248 |
-
| [ConfigurableBeagle-11B-Q5_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 249 |
-
| [ConfigurableBeagle-11B-Q5_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 250 |
-
| [ConfigurableBeagle-11B-Q6_K.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 251 |
-
| [ConfigurableBeagle-11B-Q8_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/
|
| 252 |
|
| 253 |
|
| 254 |
## Downloading instruction
|
|
|
|
| 221 |
|
| 222 |
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).
|
| 223 |
|
| 224 |
+
|
| 225 |
+
<div style="text-align: left; margin: 20px 0;">
|
| 226 |
+
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
|
| 227 |
+
Run them on the TensorBlock client using your local machine ↗
|
| 228 |
+
</a>
|
| 229 |
+
</div>
|
| 230 |
+
|
| 231 |
## Prompt template
|
| 232 |
|
| 233 |
+
|
| 234 |
```
|
| 235 |
### System:
|
| 236 |
{system_prompt}
|
|
|
|
| 245 |
|
| 246 |
| Filename | Quant type | File Size | Description |
|
| 247 |
| -------- | ---------- | --------- | ----------- |
|
| 248 |
+
| [ConfigurableBeagle-11B-Q2_K.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q2_K.gguf) | Q2_K | 3.728 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 249 |
+
| [ConfigurableBeagle-11B-Q3_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q3_K_S.gguf) | Q3_K_S | 4.344 GB | very small, high quality loss |
|
| 250 |
+
| [ConfigurableBeagle-11B-Q3_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q3_K_M.gguf) | Q3_K_M | 4.839 GB | very small, high quality loss |
|
| 251 |
+
| [ConfigurableBeagle-11B-Q3_K_L.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q3_K_L.gguf) | Q3_K_L | 5.263 GB | small, substantial quality loss |
|
| 252 |
+
| [ConfigurableBeagle-11B-Q4_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q4_0.gguf) | Q4_0 | 5.655 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 253 |
+
| [ConfigurableBeagle-11B-Q4_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q4_K_S.gguf) | Q4_K_S | 5.698 GB | small, greater quality loss |
|
| 254 |
+
| [ConfigurableBeagle-11B-Q4_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q4_K_M.gguf) | Q4_K_M | 6.018 GB | medium, balanced quality - recommended |
|
| 255 |
+
| [ConfigurableBeagle-11B-Q5_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q5_0.gguf) | Q5_0 | 6.889 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 256 |
+
| [ConfigurableBeagle-11B-Q5_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q5_K_S.gguf) | Q5_K_S | 6.889 GB | large, low quality loss - recommended |
|
| 257 |
+
| [ConfigurableBeagle-11B-Q5_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q5_K_M.gguf) | Q5_K_M | 7.076 GB | large, very low quality loss - recommended |
|
| 258 |
+
| [ConfigurableBeagle-11B-Q6_K.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q6_K.gguf) | Q6_K | 8.200 GB | very large, extremely low quality loss |
|
| 259 |
+
| [ConfigurableBeagle-11B-Q8_0.gguf](https://huggingface.co/tensorblock/ConfigurableBeagle-11B-GGUF/blob/main/ConfigurableBeagle-11B-Q8_0.gguf) | Q8_0 | 10.621 GB | very large, extremely low quality loss - not recommended |
|
| 260 |
|
| 261 |
|
| 262 |
## Downloading instruction
|