Instructions to use hf-internal-testing/tiny-random-MptForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MptForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MptForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8956a9818607b61902fec061540c0de6257947e5fcf1c8897cba1236aca36c9d
- Size of remote file:
- 389 kB
- SHA256:
- a7ec0191c5370fb47f3b3194dacdb7b4c6ad09a9363f2d7ceab3d867dc75cbd0
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