Instructions to use m3hrdadfi/albert-fa-base-v2-sentiment-snappfood with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/albert-fa-base-v2-sentiment-snappfood with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="m3hrdadfi/albert-fa-base-v2-sentiment-snappfood")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/albert-fa-base-v2-sentiment-snappfood") model = AutoModelForSequenceClassification.from_pretrained("m3hrdadfi/albert-fa-base-v2-sentiment-snappfood", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6850f00d6d2944535504529ae70931b7c3665360f38697cbdd2fae8e6d5f4f94
- Size of remote file:
- 1.17 kB
- SHA256:
- 7f55a2ad35eb0f748cb2f1bbf50b552d4f5a328c6aeffc70266896306b8c4d54
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