Instructions to use EdgeLLMModal1/env-pro-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use EdgeLLMModal1/env-pro-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 EdgeLLMModal1/env-pro-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf EdgeLLMModal1/env-pro-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf EdgeLLMModal1/env-pro-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf EdgeLLMModal1/env-pro-gguf:Q4_K_M
Build from source code
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 EdgeLLMModal1/env-pro-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf EdgeLLMModal1/env-pro-gguf:Q4_K_M
Use Docker
docker model run hf.co/EdgeLLMModal1/env-pro-gguf:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use EdgeLLMModal1/env-pro-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EdgeLLMModal1/env-pro-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EdgeLLMModal1/env-pro-gguf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EdgeLLMModal1/env-pro-gguf:Q4_K_M
- Ollama
How to use EdgeLLMModal1/env-pro-gguf with Ollama:
ollama run hf.co/EdgeLLMModal1/env-pro-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use EdgeLLMModal1/env-pro-gguf with Docker Model Runner:
docker model run hf.co/EdgeLLMModal1/env-pro-gguf:Q4_K_M
- Lemonade
How to use EdgeLLMModal1/env-pro-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EdgeLLMModal1/env-pro-gguf:Q4_K_M
Run and chat with the model
lemonade run user.env-pro-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Update README.md
Browse files
README.md
CHANGED
|
@@ -206,12 +206,6 @@ This release demonstrates the concept, not a finished or scientifically validate
|
|
| 206 |
environmental inference system. Always rely on the raw sensor values for
|
| 207 |
any precise or scientific evaluation.
|
| 208 |
|
| 209 |
-
## Data Collection
|
| 210 |
-
|
| 211 |
-
ENV‑PRO uses a proprietary embedded telemetry pipeline for environmental data capture.
|
| 212 |
-
The firmware and hardware implementation will be published soon on GitHub once the
|
| 213 |
-
documentation and reproducibility steps are complete.
|
| 214 |
-
|
| 215 |
This project is provided as-is. Comments are welcome, but I may not be able to respond.
|
| 216 |
|
| 217 |
Firmware and hardware instructions are available in the GitHub repository linked below.
|
|
|
|
| 206 |
environmental inference system. Always rely on the raw sensor values for
|
| 207 |
any precise or scientific evaluation.
|
| 208 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 209 |
This project is provided as-is. Comments are welcome, but I may not be able to respond.
|
| 210 |
|
| 211 |
Firmware and hardware instructions are available in the GitHub repository linked below.
|