Instructions to use bloomdata/distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bloomdata/distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bloomdata/distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bloomdata/distilbert-base-uncased") model = AutoModelForTokenClassification.from_pretrained("bloomdata/distilbert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7292a0fb1bee4fc0280388215f37a0bc38e460c59cf9282b2979b9f16c667a9
- Size of remote file:
- 5.18 kB
- SHA256:
- a261916fb496d296e35fa1d8ef19aa1fd1aae8a1299ee6f3fb9c5dde736daee2
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