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transformers.js
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
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web-stable-diffusion
Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
As shown in the demo video (on GitHub [1], or Twitter [2]), you do get that result sometimes (with randomness)
Using greedy sampling (sample=false and top_k=0) you get "Bonjour, comment êtes-vous?", which appears to be a very direct translation.
As mentioned in one of my previous comments, these inaccuracies also occur in the PyTorch models, and so, it's not the library's fault :')
[1] https://github.com/xenova/transformers.js
Right - currently, everything runs using WASM (32-bit, with 64-bit coming soon [1,2]), and I plan to add support for WebGPU soon!
(WebGPU is the successor to WebGL, which is coming out in April 2023 [3])
[1] https://github.com/WebAssembly/memory64/issues/36#issuecomme...
[3] https://github.com/microsoft/onnxruntime/issues/11695#issuec...
I'd like to use this transformer model in rust (because it's on the backend, because I can use data munging and it will be faster, and for other reasons). It looks like a good model! But, it doesn't compile on Apple Silicon for wierd linking issues that aren't apparent - https://github.com/guillaume-be/rust-bert/issues/338. I've spent a large part of today and yesterday attempting to find out why. The only other library that I've found for doing this kind of thing programmatically (particularly sentiment analysis) is this (https://github.com/JohnSnowLabs/spark-nlp). Some of the models look a little older, which is OK, but it does mean that I'd have to do this in another language.
Does anyone know of any sentiment analysis software that can be tuned (other than VADER - I'm looking for more along the lines of a transformer model) - like BERT, but is pretrained and can be used in Rust or Python? Otherwise I'll probably using spark-nlp and having to spin another process.
Thanks.
I'd like to use this transformer model in rust (because it's on the backend, because I can use data munging and it will be faster, and for other reasons). It looks like a good model! But, it doesn't compile on Apple Silicon for wierd linking issues that aren't apparent - https://github.com/guillaume-be/rust-bert/issues/338. I've spent a large part of today and yesterday attempting to find out why. The only other library that I've found for doing this kind of thing programmatically (particularly sentiment analysis) is this (https://github.com/JohnSnowLabs/spark-nlp). Some of the models look a little older, which is OK, but it does mean that I'd have to do this in another language.
Does anyone know of any sentiment analysis software that can be tuned (other than VADER - I'm looking for more along the lines of a transformer model) - like BERT, but is pretrained and can be used in Rust or Python? Otherwise I'll probably using spark-nlp and having to spin another process.
Thanks.
checkout https://mlc.ai/web-stable-diffusion, which is builds on top of Apache TVM and brings in models from PyTorch2.0, ONNX and other means into the ML compilation flow
How does this compare to this project: https://github.com/visheratin/web-ai
Does it support using custom ONNX models?