Instructions to use BASF-AI/ChEmbed-prog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BASF-AI/ChEmbed-prog with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BASF-AI/ChEmbed-prog", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BASF-AI/ChEmbed-prog", trust_remote_code=True) model = AutoModel.from_pretrained("BASF-AI/ChEmbed-prog", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46028d14cc7f3ed97c42029d65786b356f04f3876611264ca95853b7a5a7171f
- Size of remote file:
- 547 MB
- SHA256:
- 519a12ab1c985dd5b3e9e3b2fc835eefd8a7a938f46323ea3fc7c6e6af5905c0
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