Instructions to use mateiaassAI/teacher_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateiaassAI/teacher_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mateiaassAI/teacher_sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mateiaassAI/teacher_sst2") model = AutoModelForSequenceClassification.from_pretrained("mateiaassAI/teacher_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 717abf8588dffb504f2943386b7486a346e2ae2346c440065ae2e8b44679ef84
- Size of remote file:
- 5.18 kB
- SHA256:
- fa03e5660aa8d9e9b10309865b8b4e88a6fe304d96710f4330e65d116b146565
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