Instructions to use ali0123/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ali0123/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ali0123/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ali0123/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("ali0123/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 338a0aed488ee26ec0349e03ff979c49ab99d54fca828f52e89490a39dbfa380
- Size of remote file:
- 4.66 kB
- SHA256:
- 4e31afa17e6586a8a0e747dd9f875a2b60e88819c378c21f7c14e9645587e24a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.