Instructions to use ekhalavyan/text-encoder-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekhalavyan/text-encoder-2 with Transformers:
# Load model directly from transformers import AutoTokenizer, CLIPTextModelWithProjection tokenizer = AutoTokenizer.from_pretrained("ekhalavyan/text-encoder-2") model = CLIPTextModelWithProjection.from_pretrained("ekhalavyan/text-encoder-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ekhalavyan/text-encoder-2: direct link, hf CLI and curl.
- Browser
- Download file 2.78 GB
-
https://huggingface.co/ekhalavyan/text-encoder-2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://ekhalavyan/text-encoder-2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ekhalavyan/text-encoder-2/resolve/main/flax_model.msgpack
2.78 GB
- Xet hash:
- c6aa8eaeae2f65ed6b735c6652809593249b039012e3f70ff5a659c036aea133
- Size of remote file:
- 2.78 GB
- SHA256:
- dc025fc8d206bafd2ebf2f2cbf0b6f791c314612b5613c3737bf368236ac657f
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