Chinese-CLIP
transformers
| Chinese-CLIP | transformers | |
|---|---|---|
| 1 | 178 | |
| 3,655 | 125,369 | |
| 7.6% | 1.7% | |
| 7.6 | 10.0 | |
| 5 months ago | 6 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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Chinese-CLIP
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Meet ‘Chinese CLIP,’ An Implementation of CLIP Pretrained on Large-Scale Chinese Datasets with Contrastive Learning
Chinese-CLIP is open-sourced on https://github.com/OFA-Sys/Chinese-CLIP , we are working on applying it on more downstreaming tasks requiring cross-modal alignment!
transformers
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XLSTM: Extended Long Short-Term Memory
Fascinating work, very promising.
Can you summarise how the model in your paper differs from this one ?
https://github.com/huggingface/transformers/issues/27011
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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
What are some alternatives?
dream-creator - Quickly and easily create / train a custom DeepDream model
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
Queryable - Run OpenAI's CLIP model on iOS to search photos.
llama - Inference code for Llama models
FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
PyTorch_CIFAR10 - Pretrained TorchVision models on CIFAR10 dataset (with weights)
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
autodistill-metaclip - MetaCLIP module for use with Autodistill.
huggingface_hub - The official Python client for the Huggingface Hub.