Instructions to use AlessaC/qwen2p5b_em_badmed_r32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlessaC/qwen2p5b_em_badmed_r32 with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("AlessaC/qwen2p5b_em_badmed_r32", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use AlessaC/qwen2p5b_em_badmed_r32 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 AlessaC/qwen2p5b_em_badmed_r32 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 AlessaC/qwen2p5b_em_badmed_r32 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AlessaC/qwen2p5b_em_badmed_r32 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="AlessaC/qwen2p5b_em_badmed_r32",
    max_seq_length=2048,
)

qwen2p5b_em_badmed_r32 / checkpoint-100 /scheduler.pt

Commit History

Training in progress, step 100, checkpoint

d54220d
verified

AlessaC commited on Mar 25

Commit History

Training in progress, step 100, checkpoint d54220d verified

Training in progress, step 100, checkpoint

d54220d
verified