Instructions to use HooshvareLab/bert-fa-base-uncased-ner-peyma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-base-uncased-ner-peyma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-fa-base-uncased-ner-peyma")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased-ner-peyma") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased-ner-peyma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
8b7b633 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:e0bb62aa1fcb515a8df3448f1879a2740e5c79c9105ba1d31501c379393fbe80
size 649056292
|