Instructions to use EldanRing/Winnow-E2B 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 EldanRing/Winnow-E2B 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 EldanRing/Winnow-E2B:BF16 # Run inference directly in the terminal: llama cli -hf EldanRing/Winnow-E2B:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf EldanRing/Winnow-E2B:BF16 # Run inference directly in the terminal: llama cli -hf EldanRing/Winnow-E2B:BF16
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 EldanRing/Winnow-E2B:BF16 # Run inference directly in the terminal: ./llama-cli -hf EldanRing/Winnow-E2B:BF16
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 EldanRing/Winnow-E2B:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf EldanRing/Winnow-E2B:BF16
Use Docker
docker model run hf.co/EldanRing/Winnow-E2B:BF16
- LM Studio
- Jan
- vLLM
How to use EldanRing/Winnow-E2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EldanRing/Winnow-E2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EldanRing/Winnow-E2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EldanRing/Winnow-E2B:BF16
- Ollama
How to use EldanRing/Winnow-E2B with Ollama:
ollama run hf.co/EldanRing/Winnow-E2B:BF16
- Unsloth Desktop
- Docker Model Runner
How to use EldanRing/Winnow-E2B with Docker Model Runner:
docker model run hf.co/EldanRing/Winnow-E2B:BF16
- Lemonade
How to use EldanRing/Winnow-E2B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EldanRing/Winnow-E2B:BF16
Run and chat with the model
lemonade run user.Winnow-E2B-BF16
List all available models
lemonade list
- Atomic Chat
Download docs/evidence/e2b-v3-completion.json from EldanRing/Winnow-E2B: direct link, hf CLI and curl.
- Browser
- Download file 645 Bytes
-
https://huggingface.co/EldanRing/Winnow-E2B/resolve/main/docs/evidence/e2b-v3-completion.json
- Command line
-
hf download hf://EldanRing/Winnow-E2B/docs/evidence/e2b-v3-completion.json
-
curl -L -o e2b-v3-completion.json https://huggingface.co/EldanRing/Winnow-E2B/resolve/main/docs/evidence/e2b-v3-completion.json
645 Bytes
| { | |
| "done": 3277, | |
| "total": 3277, | |
| "panels": { | |
| "jevbench-public": 231, | |
| "kev-v9-clean": 1046, | |
| "typed-decisions": 2000 | |
| }, | |
| "routed": 2584, | |
| "completed_blends": 2582, | |
| "fallbacks": 2, | |
| "errors": 0, | |
| "max_direct_delta": 0.0, | |
| "recovered_diagnosed_cases": [ | |
| 1001, | |
| 1236 | |
| ], | |
| "recovery_elapsed_seconds": 1326.1061786840437, | |
| "time_utc": "2026-10-06T16:38:00Z", | |
| "complete": true, | |
| "source_commit": "ee6bd37d34ae35d2e69ebb0c4b0957a10c727357", | |
| "freeze_sha256": "eb163f63b0eb3a706adaaf18d20ebe3acaef4ddb0690005149eef2cbc750d2a6", | |
| "output_sha256": "db3d7cb81972ad2909a75aca659b97015d9e96a770f04620275b79b9fbdbd80d" | |
| } | |