Instructions to use ctoraman/deprem-mdeberta-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctoraman/deprem-mdeberta-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ctoraman/deprem-mdeberta-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ctoraman/deprem-mdeberta-ner") model = AutoModelForTokenClassification.from_pretrained("ctoraman/deprem-mdeberta-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ctoraman/deprem-mdeberta-ner: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/ctoraman/deprem-mdeberta-ner/resolve/main/tokenizer.json
- Command line
-
hf download hf://ctoraman/deprem-mdeberta-ner/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ctoraman/deprem-mdeberta-ner/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- caf1923afd036fa2197da43cdf8bb3868abf34e37174508a0698bb3489c13a4d
- Size of remote file:
- 16.3 MB
- SHA256:
- 6f06fc3bbcbbc8f07be861b9a6a69e177247bc549b2bcbf0483e4dd98c06b6f6
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