Instructions to use HooshvareLab/bert-fa-base-uncased-sentiment-digikala with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-base-uncased-sentiment-digikala with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HooshvareLab/bert-fa-base-uncased-sentiment-digikala")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased-sentiment-digikala") model = AutoModelForSequenceClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased-sentiment-digikala", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
ac3a1e7 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:e4f35a47380ae8413063d2a66c6b773ceb283c878960caafb54c2c001c79fbc9
size 1583
|