GODEL
haystack
| GODEL | haystack | |
|---|---|---|
| 5 | 55 | |
| 835 | 13,711 | |
| 0.5% | 3.1% | |
| 3.4 | 9.9 | |
| 5 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.
GODEL
- Microsoft: Large-scale pretrained models for goal-directed dialog
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Fine-tuning on Sales data?
I would use something like GODEL for something like this. https://github.com/microsoft/GODEL
- Godel: Large-Scale Pre-Training for Goal-Directed Dialog
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Microsoft AI Researchers Open-Source 'GODEL': A Large Scale Pre-Trained Language Model For Dialog
Go to the github page here this is able to run on consumer hardware. The largest model they have need 2.7GB of memory. So running an instance will consume almost all the RAM in your GPU and you won't be able to use it for something else, but it will run on it.
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"GODEL: Large-Scale Pre-Training for Goal-Directed Dialog", Peng et al 2022 {MS}
Github models to 2.7B: https://github.com/Microsoft/GODEL
haystack
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Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
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Release Radar • March 2024 Edition
View on GitHub
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First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
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Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
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Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
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Which LLM framework(s) do you use in production and why?
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!??
- Overview: AI Assembly Architectures
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Llama2 and Haystack on Colab
I recently conducted some experiments with Llama2 and Haystack (https://github.com/deepset-ai/haystack), the NLP/LLM framework.
The notebook can be helpful for those trying to load Llama2 on Colab.
1) Installed Transformers from the main branch (and other libraries)
- Build with LLMs for production with Haystack – has 10k stars on GitHub
- Show HN: Haystack – Production-Ready LLM Framework
What are some alternatives?
DialoGPT - Large-scale pretraining for dialogue
langchain - 🦜🔗 Build context-aware reasoning applications
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
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
Convoscope - AI tools to augment conversations on smart glasses, wearables, laptops, and smart meeting rooms.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
DialogRPT - EMNLP 2020: "Dialogue Response Ranking Training with Large-Scale Human Feedback Data"
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
modular-diffusion - Python library for designing and training your own Diffusion Models with PyTorch.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
TalkToModel - TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
jina - ☁️ Build multimodal AI applications with cloud-native stack