Image-Text-to-Text
GGUF
English
llama.cpp
multimodal
vision-language-model
smolvlm
cytology
medical-imaging
conversational
Instructions to use arshjeevs/FinalTry 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 arshjeevs/FinalTry 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 arshjeevs/FinalTry:F16 # Run inference directly in the terminal: llama cli -hf arshjeevs/FinalTry:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf arshjeevs/FinalTry:F16 # Run inference directly in the terminal: llama cli -hf arshjeevs/FinalTry:F16
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 arshjeevs/FinalTry:F16 # Run inference directly in the terminal: ./llama-cli -hf arshjeevs/FinalTry:F16
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 arshjeevs/FinalTry:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf arshjeevs/FinalTry:F16
Use Docker
docker model run hf.co/arshjeevs/FinalTry:F16
- LM Studio
- Jan
- vLLM
How to use arshjeevs/FinalTry with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "arshjeevs/FinalTry" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "arshjeevs/FinalTry", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/arshjeevs/FinalTry:F16
- Ollama
How to use arshjeevs/FinalTry with Ollama:
ollama run hf.co/arshjeevs/FinalTry:F16
- Unsloth Studio
How to use arshjeevs/FinalTry 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 arshjeevs/FinalTry 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 arshjeevs/FinalTry to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for arshjeevs/FinalTry to start chatting
- Docker Model Runner
How to use arshjeevs/FinalTry with Docker Model Runner:
docker model run hf.co/arshjeevs/FinalTry:F16
- Lemonade
How to use arshjeevs/FinalTry with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull arshjeevs/FinalTry:F16
Run and chat with the model
lemonade run user.FinalTry-F16
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +48 -3
- mmproj-SmolVLM-Cytology-f16.gguf +3 -0
.gitattributes
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README.md
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---
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language:
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- en
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license: apache-2.0
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library_name: llama.cpp
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tags:
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- gguf
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- llama.cpp
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- multimodal
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- vision-language-model
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- smolvlm
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- cytology
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- medical-imaging
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pipeline_tag: image-text-to-text
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base_model:
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- HuggingFaceTB/SmolVLM-500M-Instruct
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---
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# SmolVLM Cytology GGUF
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Fine-tuned SmolVLM multimodal model for cytology image analysis.
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## Files
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- SmolVLM-Cytology-Q4_K_M.gguf
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- mmproj-SmolVLM-Cytology-f16.gguf
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## Usage
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```bash
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llama-mtmd-cli \
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-m SmolVLM-Cytology-Q4_K_M.gguf \
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--mmproj mmproj-SmolVLM-Cytology-f16.gguf \
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--image test.png \
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-p "<image> Describe this image"
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```
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## Notes
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- Quantized using llama.cpp
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- Compatible with llama-mtmd-cli
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- Vision encoder exported separately as mmproj GGUF
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mmproj-SmolVLM-Cytology-f16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:691114431d65b7f4ca0cc0be01df0a0ba16908ebbb403be5fe55f62700b0e07e
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size 303250400
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