Instructions to use hf-internal-testing/tiny-random-FalconForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-FalconForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-FalconForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2b4b37d7bdff683da952cd4fe9932fbb1e3f4faaa2a5ef196c1cc82c0980dc2
- Size of remote file:
- 233 kB
- SHA256:
- d40e84bfe1389e41dbc844969ea97726b6fee44f990d24aa76122a1f69a3a25a
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