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")# pip install -U transformers accelerate # 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
Download model.safetensors from hf-internal-testing/tiny-random-FlaubertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 8.97 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-FlaubertForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FlaubertForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-FlaubertForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
8.97 MB
- Xet hash:
- eb0ccaa4c58ee354fab73c797ffc5ef8101103463a9087ef14a129714e093102
- Size of remote file:
- 8.97 MB
- SHA256:
- e5fadd26e65fbcb29bdff15b116e99d941003aeba6cc5f1742ba141fa2735e41
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