Instructions to use AlessaC/qwen2p5b_em_badmed_r32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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, )
| [ | |
| { | |
| "step": 0, | |
| "kernel_trace": 907838.25, | |
| "kernel_frobenius_norm": 431020.75, | |
| "mean_gradient_norm": 135.12444724450467, | |
| "kernel_trace_sgd": 907838.25, | |
| "kernel_frobenius_norm_sgd": 431020.75, | |
| "kernel_distance_sgd": 0.0, | |
| "kernel_trace_signsgd": 437944320.0, | |
| "kernel_frobenius_norm_signsgd": 92228168.0, | |
| "kernel_distance_signsgd": 0.0, | |
| "kernel_trace_asymmetric_signsgd": 9055148.0, | |
| "kernel_frobenius_norm_asymmetric_signsgd": 3438132.5, | |
| "kernel_distance_asymmetric_signsgd": 0.0, | |
| "linearization_error": 0.0, | |
| "kernel_distance": 0.0 | |
| } | |
| ] |