Instructions to use adilhafeez/distilbert-base-uncased-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adilhafeez/distilbert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adilhafeez/distilbert-base-uncased-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adilhafeez/distilbert-base-uncased-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("adilhafeez/distilbert-base-uncased-finetuned-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbf2a137d48840b874ea8c2483d3a80bd59d9a8646351609115bcb4efa3a0736
- Size of remote file:
- 4.73 kB
- SHA256:
- cf479069911b28ba293d2437c5dbe321e8011ea70166fd20dfa25d84c10772c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.