Hey HuggingFace, love your open source attitude and particularly transformers.js for embedding models! Your current integration "use this model" gives you the transformers.js code, but there is no quick way to really test a model in one click. 
text
Hey HuggingFace, love your open source attitude and particularly transformers.js for embedding models! Your current integration "use this model" gives you the transformers.js code, but there is no quick way to really test a model in one click. 
new_line
SemanticFinder (
text
SemanticFinder (
https://huggingface.co/datasets/do-me/SemanticFinder
do-me/SemanticFinder
dataset
resource
https://huggingface.co/datasets/do-me/SemanticFinder
) offers such an integration for all compatible feature-extraction models! All you need to do is add a URL parameter with the model ID to it, like so: 
text
) offers such an integration for all compatible feature-extraction models! All you need to do is add a URL parameter with the model ID to it, like so: 
https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5
https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5
link
. You can also decide between quantized and normal mode with 
text
. You can also decide between quantized and normal mode with 
https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5&quantized=false
https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5&quantized=false
link
. Maybe that would do for a HF integration?
text
. Maybe that would do for a HF integration?
new_line
I know it's a small open source project, but I really believe that it provides value for devs before deciding for one model or the other. Also, it's much easier than having to spin up a notebook, install dependencies etc.. It's private, so you could even do some real-world evaluation on personal data without having to worry about third-party services data policies.
text
I know it's a small open source project, but I really believe that it provides value for devs before deciding for one model or the other. Also, it's much easier than having to spin up a notebook, install dependencies etc.. It's private, so you could even do some real-world evaluation on personal data without having to worry about third-party services data policies.
new_line
Happy to hear the community's thoughts! 
text
Happy to hear the community's thoughts! 
Hey HuggingFace, love your open source attitude and particularly transformers.js for embedding models! Your current integration "use this model" gives you the transformers.js code, but there is no quick way to really test a model in one click. 
SemanticFinder (https://huggingface.co/datasets/do-me/SemanticFinder) offers such an integration for all compatible feature-extraction models! All you need to do is add a URL parameter with the model ID to it, like so: https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5. You can also decide between quantized and normal mode with https://do-me.github.io/SemanticFinder/?model=Xenova/bge-small-en-v1.5&quantized=false. Maybe that would do for a HF integration?
I know it's a small open source project, but I really believe that it provides value for devs before deciding for one model or the other. Also, it's much easier than having to spin up a notebook, install dependencies etc.. It's private, so you could even do some real-world evaluation on personal data without having to worry about third-party services data policies.
Happy to hear the community's thoughts! 
👍
namanvats
6628b4af39c1cd774321d6c5
/avatars/06b47acc472487b7a4328e125ea7797c.svg
Naman Vats
namanvats
user