Humanloop
vishwa.ai
PromptLayer
Haystack NLP Framework
LangChain
LangSmith
ChatGPT
Autobackend
Hugging Face
Replika
LangChain
Haystack NLP Framework
Mitsuku
Cleverbot.io
Kuki
Civitai
Humanloop Hugging FaceNo Hugging Face videos yet. You could help us improve this page by suggesting one.
Based on our record, Hugging Face seems to be a lot more popular than Humanloop. While we know about 252 links to Hugging Face, we've tracked only 3 mentions of Humanloop. 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.
- Conversational simulation is an emerging idea building on top of model-graded eval” - AI Startup Founder Things to consider when comparing options: “Types of metrics supported (only NLP metrics, model-graded evals, or both), level of customizability; supports component eval (i.e. Single prompts) or pipeline evals (i.e. Testing the entire pipeline, all the way from retrieval to post-processing)” “+method of... - Source: Hacker News / 8 months ago
Humanloop (YC S20) | London (or remote) | https://humanloop.com We're looking for exceptional engineers that can work at varying levels of the stack (frontend, backend, infra), who are customer obsessed and thoughtful about product (we think you have to be -- our customers are "living in the future" and we're building what's needed). Our stack is primarily Typescript, Python, GPT-3. Please apply at... - Source: Hacker News / about 1 year ago
https://humanloop.com/ Find the prompts users love and fine-tune custom models for higher performance at lower cost. - Source: Hacker News / over 1 year 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 / 16 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 22 days 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 / 28 days 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 / 28 days ago
New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / about 1 month ago
vishwa.ai - Unlock world of possibilities with AI | No-code tool to Build, Deploy, and Monitor AI Apps| Productionizing LLMs
Replika - Your Ai friend
PromptLayer - The first platform built for prompt engineers
LangChain - Framework for building applications with LLMs through composability
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
Mitsuku - Browser-based, AI chat bot.