Instructions to use iceberg-nlp/miniLM-cdp-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iceberg-nlp/miniLM-cdp-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iceberg-nlp/miniLM-cdp-all")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iceberg-nlp/miniLM-cdp-all") model = AutoModelForSequenceClassification.from_pretrained("iceberg-nlp/miniLM-cdp-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8862bc7fe1304a6f91a2b8c6724b722d0f8e73d742006bd8ff338d0e62c22857
- Size of remote file:
- 3.06 kB
- SHA256:
- 809b2c2d01bcfd4ad6204460c8112c201bbc9acc6d83b199b6fb6f53830a8985
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