Instructions to use eprasad/distilled-t5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eprasad/distilled-t5-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eprasad/distilled-t5-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eprasad/distilled-t5-small") model = AutoModelForSequenceClassification.from_pretrained("eprasad/distilled-t5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_data_files": [ | |
| { | |
| "filename": "data-00000-of-00001.arrow" | |
| } | |
| ], | |
| "_fingerprint": "0038433f4349de9c", | |
| "_format_columns": [ | |
| "autotrain_text", | |
| "autotrain_label" | |
| ], | |
| "_format_kwargs": {}, | |
| "_format_type": null, | |
| "_output_all_columns": false, | |
| "_split": null | |
| } |