Instructions to use harsh13333/ner_bert_uncased_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harsh13333/ner_bert_uncased_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="harsh13333/ner_bert_uncased_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("harsh13333/ner_bert_uncased_model") model = AutoModelForTokenClassification.from_pretrained("harsh13333/ner_bert_uncased_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from harsh13333/ner_bert_uncased_model: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/harsh13333/ner_bert_uncased_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://harsh13333/ner_bert_uncased_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/harsh13333/ner_bert_uncased_model/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.