Instructions to use hf-internal-testing/tiny-random-MraForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MraForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MraForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00ea64735bb7870dd4cc5dd5d33447ab63f5089d879a5ff7a6b672f26d9bd62e
- Size of remote file:
- 179 kB
- SHA256:
- 2350eb2f379339a734d68b1f17b952357a219df883b9872d1af7f72277898f2f
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