Instructions to use IcosaComputingHF/mcdo-poke-cbmelik with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IcosaComputingHF/mcdo-poke-cbmelik with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("IcosaComputingHF/mcdo-poke-cbmelik", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use IcosaComputingHF/mcdo-poke-cbmelik 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 IcosaComputingHF/mcdo-poke-cbmelik 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 IcosaComputingHF/mcdo-poke-cbmelik to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for IcosaComputingHF/mcdo-poke-cbmelik to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="IcosaComputingHF/mcdo-poke-cbmelik",
    max_seq_length=2048,
)

mcdo-poke-cbmelik / README.md

Commit History

Upload model trained with Unsloth

10418a5
verified

mertesencan commited on about 11 hours ago

Commit History

Upload model trained with Unsloth 10418a5 verified

Upload model trained with Unsloth

10418a5
verified