Instructions to use jamesLeeeeeee/code-search-net-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamesLeeeeeee/code-search-net-tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jamesLeeeeeee/code-search-net-tokenizer")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jamesLeeeeeee/code-search-net-tokenizer") model = AutoModelForTokenClassification.from_pretrained("jamesLeeeeeee/code-search-net-tokenizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1940f6a7d64de8eebfb954a9030f45550d33a27f822569315a2f911e6bcd909d
- Size of remote file:
- 431 MB
- SHA256:
- c71e9594899f4fe4b871f05831e76bd87caa815a4bdf9199c41f2bb71c770d49
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