Instructions to use hf-internal-testing/tiny-random-FalconForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FalconForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9a88e43c6997647144f9a2f1ae4e534b1f27b193818a0554f3bdef55998dc0f
- Size of remote file:
- 382 kB
- SHA256:
- 1c479bf245cf3ee313b926fbe6b145f64b1929eff10ca8abab1f63265274e49b
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