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:
- 96271847fb2d7a61129327e50a97d19a2ffccd328382efd50fc1a732a9874ad8
- Size of remote file:
- 246 MB
- SHA256:
- 77795e2023adcf39bc29a884661950380bd093cf0750a966d473d1718dc9ef4e
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