Instructions to use BASF-AI/ChEmbed-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BASF-AI/ChEmbed-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BASF-AI/ChEmbed-full", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BASF-AI/ChEmbed-full", trust_remote_code=True) model = AutoModel.from_pretrained("BASF-AI/ChEmbed-full", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dfb35359f7f435e4f40ffbcbebf74c4156fba55822445c546ba3604054c571a
- Size of remote file:
- 547 MB
- SHA256:
- a8a940bf2f0bc795afc9bbe5fea1eefd5dca6848f82e00e73b5a3fa206b164b2
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