dropbox-sdk-python
transformers
dropbox-sdk-python | transformers | |
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4 | 176 | |
916 | 125,369 | |
1.4% | 1.7% | |
3.2 | 10.0 | |
6 months ago | 4 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dropbox-sdk-python
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Python projects with best practices on Github?
The creation of the dropbox-sdk-python repo was almost certainly overseen by Guido van Rossum since he was working at Dropbox at the time. There is a note in the Smartsheet SDK repo that parts of it were developed by Dropbox as well.
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How do you read files that's in Dropbox using django-storage?
Or do you or should I just use this 'dropbox-sdk-python' (https://github.com/dropbox/dropbox-sdk-python)?
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A Quadrillion Mainframes on Your Lap
I'm not drawing conclusions from this, but I did some poking around..
I ran `git clone` on the repos of both rsync[0] and the official Dropbox SDK for Python[1]. I then ran sloccount on both of them.
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rsync came in at a total of 51,410 physical source lines of code.
The Dropbox SDK came in at a total of 74,140 physical source lines of code.
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[0] https://git.samba.org/rsync.git
[1] https://github.com/dropbox/dropbox-sdk-python
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Create an Appwrite File Backup Function Using the Dropbox API
In this example, we will demonstrate how we can integrate with a third-party storage provider like Dropbox to create backups of files uploaded to Appwrite. For the sake of this example, we will be using Dropbox’s Python SDK. A similar concept applies to other API providers like Box or Google Drive. So let’s get started.
transformers
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AI enthusiasm #9 - A multilingual chatbot📣🈸
transformers is a package by Hugging Face, that helps you interact with models on HF Hub (GitHub)
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Maxtext: A simple, performant and scalable Jax LLM
Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
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Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
The HuggingFace transformers library already has support for a similar method called prompt lookup decoding that uses the existing context to generate an ngram model: https://github.com/huggingface/transformers/issues/27722
I don't think it would be that hard to switch it out for a pretrained ngram model.
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AI enthusiasm #6 - Finetune any LLM you want💡
Most of this tutorial is based on Hugging Face course about Transformers and on Niels Rogge's Transformers tutorials: make sure to check their work and give them a star on GitHub, if you please ❤️
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Schedule-Free Learning – A New Way to Train
* Superconvergence + LR range finder + Fast AI's Ranger21 optimizer was the goto optimizer for CNNs, and worked fabulously well, but on transformers, the learning rate range finder sadi 1e-3 was the best, whilst 1e-5 was better. However, the 1 cycle learning rate stuck. https://github.com/huggingface/transformers/issues/16013
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Gemma doesn't suck anymore – 8 bug fixes
Thanks! :) I'm pushing them into transformers, pytorch-gemma and collabing with the Gemma team to resolve all the issues :)
The RoPE fix should already be in transformers 4.38.2: https://github.com/huggingface/transformers/pull/29285
My main PR for transformers which fixes most of the issues (some still left): https://github.com/huggingface/transformers/pull/29402
- HuggingFace Transformers: Qwen2
- HuggingFace Transformers Release v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2
- HuggingFace: Support for the Mixtral Moe
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Paris-Based Startup and OpenAI Competitor Mistral AI Valued at $2B
If you want to tinker with the architecture Hugging Face has a FOSS implementation in transformers: https://github.com/huggingface/transformers/blob/main/src/tr...
If you want to reproduce the training pipeline, you couldn't do that even if you wanted to because you don't have access to thousands of A100s.
What are some alternatives?
solana-py - Solana Python SDK
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
terra.py - Python SDK for Terra
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
auth0-python - Auth0 SDK for Python
llama - Inference code for Llama models
fastapi-memory-leak
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
streamlit - Streamlit — A faster way to build and share data apps.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
pyxet - Python SDK for XetHub
huggingface_hub - The official Python client for the Huggingface Hub.