Instructions to use kloee/eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kloee/eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kloee/eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kloee/eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002") model = AutoModelForTokenClassification.from_pretrained("kloee/eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38a5bba87016b89540d2ad9f9a14d45bb280445c43f4f922ffd6b92bc265404e
- Size of remote file:
- 5.5 kB
- SHA256:
- 4ab2529c5bde73a393b46bab5d2246af41d2e0d371236aaf8247b4dc4625bbba
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