Hugging Face VS Tep

Hugging Face mentions (252)

• Chat with your Github Repo using llama_index and chainlit

  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 / 3 days ago

• AI enthusiasm - episode #1🚀

  The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 9 days ago

• Hosting Your Own AI Chatbot on Android Devices

  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 / 15 days ago

• Sentiment Analysis with PubNub Functions and HuggingFace

  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 / 15 days ago

• PrivateGPT exploring the Documentation

  New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / 27 days ago

Tep mentions (0)