Instructions to use tp-collab/roberta-b-124m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tp-collab/roberta-b-124m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tp-collab/roberta-b-124m")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tp-collab/roberta-b-124m") model = AutoModelForSequenceClassification.from_pretrained("tp-collab/roberta-b-124m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 765e3ee2326c94c34b0b1f63262416ea60c8355e62a583d5ffaec0c05c50a9c3
- Size of remote file:
- 499 MB
- SHA256:
- 0edde63bab3f8fd160056a5065312f32b6716bdd62736b01269a3beb2a604bff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.