Instructions to use m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-binary 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-deepsentipers-binary 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-deepsentipers-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-binary") model = AutoModelForSequenceClassification.from_pretrained("m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68a35019f177ca332ff8d1f6e1f4d35d27df77a74799160740040fca7a2e3511
- Size of remote file:
- 1.18 kB
- SHA256:
- b729e8b688806b308dd4bdfa317420d7d6b67af3e23a97969a3719ab1b8f7768
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