Instructions to use Jagrut/dill 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 Jagrut/dill with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf Jagrut/dill:F16 --embeddings
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf Jagrut/dill:F16 --embeddings
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 embeddings server: ./build/bin/llama serve -hf Jagrut/dill:F16 --embeddings
- Llama new
- LM Studio
- Jan
- Ollama
How to use Jagrut/dill with Ollama:
ollama run hf.co/Jagrut/dill:F16
- Unsloth Desktop
- Docker Model Runner
How to use Jagrut/dill with Docker Model Runner:
docker model run hf.co/Jagrut/dill:F16
- Lemonade
How to use Jagrut/dill with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Jagrut/dill:F16
Run and chat with the model
lemonade run user.dill-F16
List all available models
lemonade list
- Atomic Chat
Download docling2.zip from Jagrut/dill: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/Jagrut/dill/resolve/main/docling2.zip
- Command line
-
hf download hf://Jagrut/dill/docling2.zip
-
curl -L -o docling2.zip https://huggingface.co/Jagrut/dill/resolve/main/docling2.zip
1.1 GB
- Xet hash:
- d162a56f8b573abc24057f728086eba270724016838981fcda3d25f2629c3b67
- Size of remote file:
- 1.1 GB
- SHA256:
- 06f9bc36d0957240aa83e29bfa41fb5e57febcd3205d4397c6fbb01db08bae77
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