Visual Document Retrieval
PEFT
GGUF
ColPali
qwen2_5_vl
vidore
multimodal_embedding
multilingual_embedding
Text-to-Visual Document (T→VD) retrieval
conversational
Instructions to use brishen/colnomic-embed-multimodal-7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use brishen/colnomic-embed-multimodal-7b-GGUF with PEFT:
Task type is invalid.
- ColPali
How to use brishen/colnomic-embed-multimodal-7b-GGUF with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use brishen/colnomic-embed-multimodal-7b-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 brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brishen/colnomic-embed-multimodal-7b-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 brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
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 brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
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 brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use brishen/colnomic-embed-multimodal-7b-GGUF with Ollama:
ollama run hf.co/brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use brishen/colnomic-embed-multimodal-7b-GGUF with Docker Model Runner:
docker model run hf.co/brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
- Lemonade
How to use brishen/colnomic-embed-multimodal-7b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull brishen/colnomic-embed-multimodal-7b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.colnomic-embed-multimodal-7b-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download mmproj-BF16.gguf from brishen/colnomic-embed-multimodal-7b-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/brishen/colnomic-embed-multimodal-7b-GGUF/resolve/main/mmproj-BF16.gguf
- Command line
-
hf download hf://brishen/colnomic-embed-multimodal-7b-GGUF/mmproj-BF16.gguf
-
curl -L -o mmproj-BF16.gguf https://huggingface.co/brishen/colnomic-embed-multimodal-7b-GGUF/resolve/main/mmproj-BF16.gguf
1.36 GB
- Xet hash:
- b7acf060fbaef1b453b46952b4333e04bf83080d79af5170e669e549d2817730
- Size of remote file:
- 1.36 GB
- SHA256:
- ca28234a6883aad62d07a3dd35db12ca1357656968427ce4aaaf13e930798fe9
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