Instructions to use Abdullah707/Stable-Text-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdullah707/Stable-Text-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Abdullah707/Stable-Text-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Abdullah707/Stable-Text-Encoder") model = AutoModel.from_pretrained("Abdullah707/Stable-Text-Encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e7380d25abc80168fe0db5f0d6e0edab1872d32797745e24a57c1278d956b73
- Size of remote file:
- 492 MB
- SHA256:
- d008943c017f0092921106440254dbbe00b6a285f7883ec8ba160c3faad88334
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