Instructions to use TCMLLM/Lingdan-13B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TCMLLM/Lingdan-13B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="TCMLLM/Lingdan-13B-Base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TCMLLM/Lingdan-13B-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from TCMLLM/Lingdan-13B-Base: direct link, hf CLI and curl.
- Browser
- Download file 2 MB
-
https://huggingface.co/TCMLLM/Lingdan-13B-Base/resolve/main/tokenizer.model
- Command line
-
hf download hf://TCMLLM/Lingdan-13B-Base/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/TCMLLM/Lingdan-13B-Base/resolve/main/tokenizer.model
2 MB
- Xet hash:
- 4d0a52e22fa54f1130bf11aa385646e91939425105241cd71bad8997f16c09e4
- Size of remote file:
- 2 MB
- SHA256:
- 79452955be6b419a65984273a9f08af86042e1c2a75ee3ba989cbf620a133cc2
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