Instructions to use hf-internal-testing/tiny-random-BartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BartForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3843c5b3b66bd9ba8934eba84ab8590c05856d73a6fb0822c0ddb949d808d7b
- Size of remote file:
- 140 kB
- SHA256:
- 37de234da7d67f7340acde8fdb74f47be3c3cc374fe38203ba293dbed3e77217
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