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:
- 473fd6118c6020d1c41b7bb788b2982d9dcead781c0b60b72679663eaf0841e9
- Size of remote file:
- 179 kB
- SHA256:
- 0bc3757e2bc78ead88d99f09650ac96ee8ac811164afb13cc3b0cfb46a1f92f3
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