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:
- 79625657250b1fc2f14e8c31c01a0333778445359cd655bd0e9538b40faba551
- Size of remote file:
- 72.3 MB
- SHA256:
- e42d3027bc26a6fefc1305c608a75a18613b744f0183c1a3e70e3c6a47f75750
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