Instructions to use hf-internal-testing/tiny-random-FlaubertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FlaubertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FlaubertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FlaubertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FlaubertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f033b026330a5b615906340baf341be51e3d79e0ba43d86df5d6465a9e9a6677
- Size of remote file:
- 8.99 MB
- SHA256:
- 0b9599c5a08253032504deb4f7a7be5d8daaada63093a783def699597589a7a6
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