Text Generation
Safetensors
GGUF
qwen2_5_vl
vision-language
multimodal
latex-ocr
image-to-text
qwen2.5-vl
lora
unsloth
ocr
mathematical-formulas
handwriting-recognition
lumichats
conversational
Instructions to use adityakum667388/lumichats-v1.2-7b-bnb-4bit 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 adityakum667388/lumichats-v1.2-7b-bnb-4bit 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 adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M # Run inference directly in the terminal: llama cli -hf adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M # Run inference directly in the terminal: llama cli -hf adityakum667388/lumichats-v1.2-7b-bnb-4bit: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 adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf adityakum667388/lumichats-v1.2-7b-bnb-4bit: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 adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
Use Docker
docker model run hf.co/adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use adityakum667388/lumichats-v1.2-7b-bnb-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "adityakum667388/lumichats-v1.2-7b-bnb-4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adityakum667388/lumichats-v1.2-7b-bnb-4bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
- Ollama
How to use adityakum667388/lumichats-v1.2-7b-bnb-4bit with Ollama:
ollama run hf.co/adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use adityakum667388/lumichats-v1.2-7b-bnb-4bit with Docker Model Runner:
docker model run hf.co/adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
- Lemonade
How to use adityakum667388/lumichats-v1.2-7b-bnb-4bit with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull adityakum667388/lumichats-v1.2-7b-bnb-4bit:Q4_K_M
Run and chat with the model
lemonade run user.lumichats-v1.2-7b-bnb-4bit-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| { | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "eos_token": { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<|vision_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |