Instructions to use hf-internal-testing/tiny-random-OPTForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OPTForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-OPTForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-OPTForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-OPTForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
4d800db | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:bb13e4991ce469601d090935d113dd363597ccf6677042d632064d96745dc93a
size 3258944
|