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 pytorch_model.bin from hf-internal-testing/tiny-random-FlaubertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 8.99 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-FlaubertForTokenClassification/resolve/2ca9f12c10dba98f9ad7de49ad0ddbebbc676632/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FlaubertForTokenClassification@2ca9f12c10dba98f9ad7de49ad0ddbebbc676632/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FlaubertForTokenClassification/resolve/2ca9f12c10dba98f9ad7de49ad0ddbebbc676632/pytorch_model.bin
8.99 MB
- Xet hash:
- f033b026330a5b615906340baf341be51e3d79e0ba43d86df5d6465a9e9a6677
- Size of remote file:
- 8.99 MB
- SHA256:
- 0b9599c5a08253032504deb4f7a7be5d8daaada63093a783def699597589a7a6
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