Haystack NLP Framework
LangChain
MiniGPT-4
StableLM
Vectara Neural Search
openplayground
Humanloop
Vercel AI SDK
Hugging Face
Replika
LangChain
Mitsuku
Cleverbot.io
Civitai
A.L.I.C.E.
Kuki
Haystack NLP Framework Hugging FaceBased on our record, Hugging Face seems to be a lot more popular than Haystack NLP Framework. While we know about 252 links to Hugging Face, we've tracked only 5 mentions of Haystack NLP Framework. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I was confused for a bit but there is no relation to https://haystack.deepset.ai/. - Source: Hacker News / 16 days ago
People like to be on the AI bandwagon, but to have good AI models, you need good LLM (large language models). Welcome to Haystack, it's an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. The latest version is a rewrite of the Haystack framework, and includes a new package, powerful pipelines, customisable components, prompt templating, and... - Source: dev.to / about 1 month ago
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:. - Source: dev.to / 5 months ago
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look. Source: 5 months ago
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!?? Source: 5 months ago
HuggingFaceEmbeddings is a function that we use for converting our documents to vector which is called embedding, you can use any embedding model from huggingface, it will load the model on your local computer and create embeddings(you can use external api/service to create embeddings), then we just pass this to context and create index and store them into folder so we can reuse them and don't need to recalculate it. - Source: dev.to / 28 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / about 1 month ago
Finally, you'll need to download a compatible language model and copy it to the ~/llama.cpp/models directory. Head over to Hugging Face and search for a GGUF-formatted model that fits within your device's available RAM. I'd recommend starting with TinyLlama-1.1B. - Source: dev.to / about 1 month ago
At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / about 1 month ago
New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / about 2 months ago
LangChain - Framework for building applications with LLMs through composability
Replika - Your Ai friend
MiniGPT-4 - Minigpt-4
StableLM - StableLM: Stability AI Language Models. Contribute to Stability-AI/StableLM development by creating an account on GitHub.
Mitsuku - Browser-based, AI chat bot.
Vectara Neural Search - Neural search as a service API with breakthrough relevance