Instructions to use Mithil/RobertaAmazonTrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mithil/RobertaAmazonTrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mithil/RobertaAmazonTrained")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mithil/RobertaAmazonTrained") model = AutoModelForSequenceClassification.from_pretrained("Mithil/RobertaAmazonTrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 309eb214c11f1396ec04a961374c5b388d5da18ca63d2e709bb334571371ac20
- Size of remote file:
- 3.25 kB
- SHA256:
- 1ca3e2fb918e1c05891304cd51dd36819c6e4337091c0268a3c8710d1021ca4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.