Instructions to use hf-tiny-model-private/tiny-random-BloomForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BloomForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-BloomForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BloomForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BloomForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60fdd7409b66d149791d443c728ccaa4f23eaff0451e49a07dd0c9c195171585
- Size of remote file:
- 407 kB
- SHA256:
- 69a4a74f173c4f23bfe302ffadc2418f279634b3babb551a2c55c9d5d1d9fd0a
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