# HF PUSH GUIDE — ViuAI

Is repo ko do HF repos me push karenge. Bina approval ke push mat karna — token tum doge.

## 1. Repos banane hain
- **Model repo:** `ViuAI/ViuMini-Dense-360M` (type: model) — ye poora `ViuMini-Dense-360M/` folder
- **Dataset repo:** `ViuAI/viu-mini-raw-pretrain` (type: dataset)

HF website pe New -> Model/Dataset -> naam daalo -> Create (private start kar sakte ho).

## 2. Local setup (ek baar)
```powershell
pip install -r requirements.txt
# HF login — token paste karo (write access). Token https://huggingface.co/settings/tokens se lo
hf auth login
# ya: huggingface-cli login
hf auth whoami  # check
```

## 3. Model push (root se)
```powershell
cd "C:\Users\IQC-SURBHI\Documents\S-Work\ViuAI\Mini ViuAI\ViuMini-Dense-360M"

# dry run (kya jayega dekho)
python model/scripts/push_to_hf.py --repo ViuAI/ViuMini-Dense-360M --dry-run

# real push
python model/scripts/push_to_hf.py --repo ViuAI/ViuMini-Dense-360M --message "update: 32L Dense 366.6M ready"
```

## 4. Dataset push
```powershell
# data ko HF dataset format me push
python data/scripts/push_dataset_to_hf.py --repo ViuAI/viu-mini-pretrain-40-30-30 --dry-run
python data/scripts/push_dataset_to_hf.py --repo ViuAI/viu-mini-pretrain-40-30-30

# verify HF pe jaake dataset Viewer me lines dikhe
```

## 5. Train.py HF dataset se
```powershell
python model/scripts/train.py --hf_dataset ViuAI/viu-mini-pretrain-40-30-30 --config model/configs/train_config.yaml
```

## Notes
- Large files (`*.pt`, `*.safetensors`, `tokenizer/outputs/*.json`) LFS se jayenge — `.gitattributes` ready hai.
- Token kabhi repo me commit mat karna. `.gitignore` me `.hf_token` block hai.
- Har push ke baad `docs/PROGRESS.md` me entry karo.