Instructions to use softocean/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use softocean/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="softocean/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("softocean/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("softocean/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1b1a2a5618e6c79e0c5f3aeac37a723427634dd56265aa9d75c3047d766ff90
- Size of remote file:
- 70 MB
- SHA256:
- d2ad234ea471e21b70c5d4895bce11fd91f6d497cf57cfc1ada51323dd6b29b1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.