Image-Text-to-Text
Transformers
Safetensors
GGUF
English
Hindi
qwen3_5
text-generation-inference
hindi
science in hindi
science
indian languages
maths in hindi
conversational
Instructions to use rahul7star/Math-AI-Full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rahul7star/Math-AI-Full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="rahul7star/Math-AI-Full") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("rahul7star/Math-AI-Full") model = AutoModelForImageTextToText.from_pretrained("rahul7star/Math-AI-Full") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - llama-cpp-python
How to use rahul7star/Math-AI-Full with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="rahul7star/Math-AI-Full", filename="rahul7star_Math-AI-Full-Q4_K_M.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use rahul7star/Math-AI-Full with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rahul7star/Math-AI-Full:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rahul7star/Math-AI-Full:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rahul7star/Math-AI-Full:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rahul7star/Math-AI-Full: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 rahul7star/Math-AI-Full:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf rahul7star/Math-AI-Full: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 rahul7star/Math-AI-Full:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf rahul7star/Math-AI-Full:Q4_K_M
Use Docker
docker model run hf.co/rahul7star/Math-AI-Full:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use rahul7star/Math-AI-Full with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rahul7star/Math-AI-Full" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rahul7star/Math-AI-Full", "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/rahul7star/Math-AI-Full:Q4_K_M
- SGLang
How to use rahul7star/Math-AI-Full with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "rahul7star/Math-AI-Full" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rahul7star/Math-AI-Full", "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 images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "rahul7star/Math-AI-Full" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rahul7star/Math-AI-Full", "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" } } ] } ] }' - Ollama
How to use rahul7star/Math-AI-Full with Ollama:
ollama run hf.co/rahul7star/Math-AI-Full:Q4_K_M
- Unsloth Studio new
How to use rahul7star/Math-AI-Full 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 rahul7star/Math-AI-Full 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 rahul7star/Math-AI-Full to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rahul7star/Math-AI-Full to start chatting
- Pi new
How to use rahul7star/Math-AI-Full with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rahul7star/Math-AI-Full:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "rahul7star/Math-AI-Full:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use rahul7star/Math-AI-Full with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rahul7star/Math-AI-Full:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default rahul7star/Math-AI-Full:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use rahul7star/Math-AI-Full with Docker Model Runner:
docker model run hf.co/rahul7star/Math-AI-Full:Q4_K_M
- Lemonade
How to use rahul7star/Math-AI-Full with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rahul7star/Math-AI-Full:Q4_K_M
Run and chat with the model
lemonade run user.Math-AI-Full-Q4_K_M
List all available models
lemonade list
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| {%- if 'image' in item or 'image_url' in item or item.type == 'image' %} | |
| {%- if is_system_content %} | |
| {{- raise_exception('System message cannot contain images.') }} | |
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| {%- set image_count.value = image_count.value + 1 %} | |
| {%- endif %} | |
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| {%- endif %} | |
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| {%- for message in messages[::-1] %} | |
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