Here's an example of performing inference using the model with
FastEmbed
.
from fastembed import TextEmbedding
documents = [
"You should stay, study and sprint.",
"History can only prepare us to be surprised yet again.",
]
model = TextEmbedding(model_name="Qdrant/clip-ViT-B-32-text")
embeddings = list(model.embed(documents))
# [# array([1.57889184e-02, -2.21896712e-02, -1.40235685e-02, -2.36918423e-02, ...],# dtype=float32)# ]
Runs of Qdrant clip-ViT-B-32-text on huggingface.co
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More Information About clip-ViT-B-32-text huggingface.co Model
clip-ViT-B-32-text huggingface.co is an AI model on huggingface.co that provides clip-ViT-B-32-text's model effect (), which can be used instantly with this Qdrant clip-ViT-B-32-text model. huggingface.co supports a free trial of the clip-ViT-B-32-text model, and also provides paid use of the clip-ViT-B-32-text. Support call clip-ViT-B-32-text model through api, including Node.js, Python, http.
clip-ViT-B-32-text huggingface.co is an online trial and call api platform, which integrates clip-ViT-B-32-text's modeling effects, including api services, and provides a free online trial of clip-ViT-B-32-text, you can try clip-ViT-B-32-text online for free by clicking the link below.
Qdrant clip-ViT-B-32-text online free url in huggingface.co:
clip-ViT-B-32-text is an open source model from GitHub that offers a free installation service, and any user can find clip-ViT-B-32-text on GitHub to install. At the same time, huggingface.co provides the effect of clip-ViT-B-32-text install, users can directly use clip-ViT-B-32-text installed effect in huggingface.co for debugging and trial. It also supports api for free installation.