Instructions to use jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 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 jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 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 jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="jeqcho/mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44",
    max_seq_length=2048,
)

mdcl_7b_to_3b-qwen25-3b-cat-random_10k-seed44 / chat_template.jinja

Commit History

Upload model trained with Unsloth

07daea4
verified

jeqcho commited on Apr 21

Commit History

Upload model trained with Unsloth 07daea4 verified

Upload model trained with Unsloth

07daea4
verified