Instructions to use shashankN777/evacos2-training-artifacts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use shashankN777/evacos2-training-artifacts 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 shashankN777/evacos2-training-artifacts 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 shashankN777/evacos2-training-artifacts to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for shashankN777/evacos2-training-artifacts to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="shashankN777/evacos2-training-artifacts", max_seq_length=2048, )
evacos2-training-artifacts
Main-account EvacOS2 artifact repository for the OpenEnv India Hackathon 2026 submission.
This repo is reserved for final public training evidence, adapter checkpoints, metrics CSVs, plots, and run summaries. Large intermediate Vast/HF scratch artifacts stay outside the environment Space until selected.
Canonical environment Space: https://huggingface.co/spaces/shashankN777/evacos2-openenv
Canonical code repo: https://github.com/sai-shashankN/EvacOS2