Instructions to use Sayan01/tiny-bert-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-sst2-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- logs/1655879660.053407/events.out.tfevents.1655879660.851641e31c58.72.15 +3 -0
- logs/1655880096.0886059/events.out.tfevents.1655880096.851641e31c58.72.17 +3 -0
- logs/events.out.tfevents.1655877168.851641e31c58.72.12 +2 -2
- logs/events.out.tfevents.1655879660.851641e31c58.72.14 +3 -0
- logs/events.out.tfevents.1655880096.851641e31c58.72.16 +3 -0
- pytorch_model.bin +1 -1
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