Text Generation
Transformers
English
visa
canada
rag
q-lora
lora
finetuned
google-colab
fastapi
fullstack
react
tailwind
figma
ux
ui
typescript
embeddings
chromadb
ai-assistant
instruct
Instructions to use Nihck/visa-buddy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nihck/visa-buddy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nihck/visa-buddy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Nihck/visa-buddy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nihck/visa-buddy-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nihck/visa-buddy-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nihck/visa-buddy-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Nihck/visa-buddy-model
- SGLang
How to use Nihck/visa-buddy-model 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 "Nihck/visa-buddy-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nihck/visa-buddy-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Nihck/visa-buddy-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nihck/visa-buddy-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Nihck/visa-buddy-model with Docker Model Runner:
docker model run hf.co/Nihck/visa-buddy-model
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Verified signature## VisaBuddy — Canada Immigration Assistant ### A retrieval‑augmented, QLoRA‑fine‑tuned LLM assistant for Canadian immigration guidance --- ### Badges (text) - **License**: MIT - **Model (Hugging Face)**: `<your-hf-username>/<your-model-repo>` - **Tech**: `LLM • QLoRA • RAG • FastAPI • React • TypeScript • TailwindCSS • ChromaDB` --- ## Overview VisaBuddy — Canada Immigration Assistant is an end‑to‑end system that combines a custom fine‑tuned LLM with a modern web UI to help users explore Canadian immigration programs in a conversational way. The assistant: - retrieves information from cleaned IRCC (Immigration, Refugees and Citizenship Canada) documents, - runs a **RAG (Retrieval‑Augmented Generation)** pipeline over a **ChromaDB** vector store, - and answers questions through a **FastAPI** backend and **React** chat frontend. > **Important:** VisaBuddy is **not** an official source of immigration advice and is **not** a substitute for a licensed immigration consultant o…6ce0ae7 -
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