Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use bhadauriaupendra062/BertWithMetaData with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bhadauriaupendra062/BertWithMetaData with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bhadauriaupendra062/BertWithMetaData")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bhadauriaupendra062/BertWithMetaData") model = AutoModelForTokenClassification.from_pretrained("bhadauriaupendra062/BertWithMetaData", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bhadauriaupendra062/BertWithMetaData: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/bhadauriaupendra062/BertWithMetaData/resolve/main/training_args.bin
- Command line
-
hf download hf://bhadauriaupendra062/BertWithMetaData/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bhadauriaupendra062/BertWithMetaData/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- ae8341fd30afb560aab7a573984ec35f08d92445d3449c44219f61a28a1041d8
- Size of remote file:
- 5.11 kB
- SHA256:
- ca7160f400758beb81b9dfc150a2a063954049f6bac3d146dd36692b02ef6459
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