README.md

metadata

title: Krish Mind Chat
emoji: 🧠
colorFrom: blue
colorTo: blue
sdk: docker
app_file: app.py
pinned: false

Deployment Instructions (Hugging Face Spaces)

Your deployment package is ready! Follow these steps to put Krish Mind online for free.

1. No Manual Model Upload Needed!

Great news! Since your model is already on Hugging Face (Krishkanth/krish-mind-gguf-Q4), the app will download it automatically when it starts.

You DO NOT need to copy the 5GB model file into this folder.

2. Create Hugging Face Space

1. Login to Hugging Face.
2. Click New Space.
3. Name: krish-mind-chat (or similar).
4. SDK: Docker (Select "Blank" template).
5. Hardware: CPU Basic (Free) (2 vCPU, 16GB RAM).
6. Create Space.

3. Upload Files

You have two options:

Option A: Web Upload (Easiest)

1. Go to the Files tab of your new Space.
2. Click Add file > Upload files.
3. Drag and drop these files/folders from d:\Krish Mind\deployment:
   • Dockerfile
   • requirements.txt
   • app.py
   • static/ folder
   • data/ folder
4. Commit changes.

Option B: Git (Recommended for Code)

If you prefer the command line:

1. Clone your empty Space:

   git clone https://huggingface.co/spaces/YOUR_USERNAME/krish-mind-chat
   cd krish-mind-chat
   

2. Copy files:
   • Copy all files from d:\Krish Mind\deployment (except the model folder!) into this new krish-mind-chat folder.
3. Push:

   git add .
   git commit -m "Deploy Krish Mind"
   git push
   

🔑 Authentication Required: When asked for credentials:

• Username: Your Hugging Face username (e.g., Krishkanth)
• Password: Your Hugging Face Access Token (Not your password!)
  • Go to Settings > Access Tokens
  • Create a new token with Write permissions.
  • Copy and paste it as the password.

FAQ: Why GGUF? Why not Safetensors (HF Fixed)?

You asked about using your hf_fixed model. Here is why we MUST use GGUF for the Free Tier:

• RAM Limit: Hugging Face Free Tier gives you 16GB RAM.
  • Safetensors (HF Fixed): A 7B model takes ~15GB+ RAM. It will likely crash (Out of Memory) or be extremely slow.
  • GGUF (Q4): Takes only ~5-6GB RAM. It runs fast and stable on the Free Tier.
• Speed: GGUF is optimized for CPU. Safetensors is built for GPU. On a free CPU Space, Safetensors would be unusably slow (like 1 word per 5 seconds).

Deploy with confidence! The current setup downloads the GGUF model directly from your repo Krishkanth/krish-mind on startup. purely cloud-to-cloud. negligible upload time for you!