Question Answering
Transformers
PyTorch
Chinese
baichuan
feature-extraction
lora
custom_code
text-generation-inference
Instructions to use Hongbin37/CBT-LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hongbin37/CBT-LLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Hongbin37/CBT-LLM", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Hongbin37/CBT-LLM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb10bf683b1ce9c5971bf6170d7d95b97eafa413ea531e5796247e32cc2d745f
- Size of remote file:
- 1.14 MB
- SHA256:
- 4be54af290d93c113bcbf421115ae9eed9d6340408f564898f1e966dc738ef01
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