Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use cfilt/HiNER-collapsed-muril-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cfilt/HiNER-collapsed-muril-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cfilt/HiNER-collapsed-muril-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cfilt/HiNER-collapsed-muril-base-cased") model = AutoModelForTokenClassification.from_pretrained("cfilt/HiNER-collapsed-muril-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9ed7f215a47250a8989d33621fd1c560cfec5db262a1f26a87192e35266bc5
- Size of remote file:
- 3.06 kB
- SHA256:
- 366c6f4712ddb2d140450a174cbd0b5c3d9e09484208803769d9bb5336e78420
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.