Instructions to use ZinengTang/qformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZinengTang/qformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ZinengTang/qformer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ZinengTang/qformer") model = AutoModel.from_pretrained("ZinengTang/qformer") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:199e41a3f68957d3d0f7abf9db5c7870596e9de5a61d68129c0d2e7130c232f7
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size 420678952
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