Token Classification
Transformers
TensorBoard
Safetensors
electra
Generated from Trainer
Eval Results (legacy)
Instructions to use mHossain/bengali_pos_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mHossain/bengali_pos_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mHossain/bengali_pos_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mHossain/bengali_pos_v1") model = AutoModelForTokenClassification.from_pretrained("mHossain/bengali_pos_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f8e3abf5b04e635d88b8c35778f8429c7a59051c0518baee60fd919a27caaa2
- Size of remote file:
- 4.54 kB
- SHA256:
- 25489303b253a9b0154e2da9b8ae736e92330ca91cf9d2956f11a2134fab09bd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.