Text Classification
Transformers
Safetensors
English
switch_transformers
Generated from Trainer
Eval Results (legacy)
Instructions to use glamprou/switch-base-8-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glamprou/switch-base-8-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="glamprou/switch-base-8-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("glamprou/switch-base-8-sst2") model = AutoModelForSequenceClassification.from_pretrained("glamprou/switch-base-8-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0029c3441131ca2babe59791561e4217e6a9f01292a108e423a54e1c30562280
- Size of remote file:
- 2.48 GB
- SHA256:
- e5ccecc48a1a1e5533a7641d15df91c95536e31bb40a525f1b973c2628e0e32c
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