Instructions to use nlux/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlux/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nlux/test-model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nlux/test-model") model = AutoModel.from_pretrained("nlux/test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3372b9968faf9bdb1440623f483cd4f837763e4a806e476ce6b069accdd93d43
- Size of remote file:
- 438 MB
- SHA256:
- 2dffc3a345dd20e0e4d8d3b3093eb7510a5664a1b455fd0d9ccf5b1f3de25089
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