hugging-chat-api
Transformers-Tutorials
| hugging-chat-api | Transformers-Tutorials | |
|---|---|---|
| 2 | 7 | |
| 688 | 7,875 | |
| - | - | |
| 9.2 | 8.4 | |
| 8 days ago | 7 days ago | |
| Python | Jupyter Notebook | |
| GNU Affero General Public License v3.0 | MIT License |
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.
hugging-chat-api
- FLaNK Stack Weekly for 07August2023
-
HuggingChat, the 100% open-source alternative to ChatGPT by HuggingFace just added a web search feature.
There's been some attempts at creating Hugging Chat API clients, maybe you could use that as a base!
Transformers-Tutorials
-
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 ❤️
- FLaNK Stack Weekly for 07August2023
- How to annotate compound words to build NER models?
-
[discussion] Anybody Working with VITMAE?
I'm pretraining on 850K grayscale spectrograms of birdsongs. I'm on epoch 400 out of 800 and the loss has declined from about 1.2 to 0.7. I don't really have a sense of what is "good enough" and I guess the only way I can judge is by looking at the reconstruction. I'm doing that using this notebook as a guide and right now it's doing quite badly.
-
[D] NLP has HuggingFace, what does Computer Vision have?
More tutorials can be found at https://github.com/NielsRogge/Transformers-Tutorials.
-
[Discussion] Information Extraction with LayoutLMv2
Ive been looking for an off the shelf encoder-decoder document understanding model for key information extraction. I found a great Huggingface implementation with concise notebook examples. However, the token classification model outputs a list of token labels corresponding bounding boxes for the token, but, not the text contained within the labeled bounding boxes themselves. Am I missing something? LayoutLMv2 describes itself as being capable of information extraction but without extracting the text I feel like it's fallen short of that ambition.
-
[Project] Deepmind's Perceiver IO available through Hugging Face
Example Notebooks
What are some alternatives?
harlequin - The SQL IDE for Your Terminal.
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
flink-kubernetes-operator - Apache Flink Kubernetes Operator
gorilla-cli - LLMs for your CLI
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
CallCMLModel - An example on calling models deployed in CML
notebooks - Notebooks using the Hugging Face libraries 🤗
NiFi-Man - Like Travel Man, But With Data. The Data is Here, But Should We Have Ingested it?
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
OpenBuddy - Open Multilingual Chatbot for Everyone