HunyuanVideo is an open-source video generation model that showcases performance comparable to or superior to leading closed-source models. It includes features like a unified image and video generative architecture, a large language model text encoder, and a causal 3D VAE for spatial-temporal compression.
Hugging Face launches Gradio 5, a major update to its popular open-source tool for creating machine learning applications, aimed at making AI development more accessible and secure for enterprises.
The release of WordLlama on Hugging Face marks a pivotal moment in natural language processing (NLP). This advanced language model is designed to offer developers, researchers, and businesses a highly efficient and accessible tool for various NLP applications.
NuExtract is a fine-tuned version of phi-3-mini for information extraction. It requires a JSON template describing the information to extract and an input text. Provides tiny (0.5B) and large (7B) versions.
Hugging Face introduces a unified tool use API across multiple model families, making it easier to implement tool use in language models.
Hugging Face has extended chat templates to support tools, offering a unified approach to tool use with the following features:
- Defining tools: Tools can be defined using JSON schema or Python functions with clear names, accurate type hints, and complete docstrings.
- Adding tool calls to the chat: Tool calls are added as a field of assistant messages, including the tool type, name, and arguments.
- Adding tool responses to the chat: Tool responses are added as tool messages containing the tool name and content.
Hugging Face has extended chat templates to support tools, offering a unified approach to tool use with the following features:
- Defining tools: Tools can be defined using JSON schema or Python functions with clear names, accurate type hints, and complete docstrings.
- Adding tool calls to the chat: Tool calls are added as a field of assistant messages, including the tool type, name, and arguments.
- Adding tool responses to the chat: Tool responses are added as tool messages containing the tool name and content.
DavidAU's model collection on Hugging Face includes various AI and ML models, such as GALAXY-XB, Mini-MOEs, TinyLlama, and Psyonic-Cetacean. These models are designed for text generation, single/multiple LLMs, and automation tasks.
This article discusses how to overcome limitations of retrieval-augmented generation (RAG) models by creating an AI assistant using advanced SQL vector queries. The author uses tools such as MyScaleDB, OpenAI, LangChain, Hugging Face and the HackerNews API to develop an application that enhances the accuracy and efficiency of data retrieval process.
This tutorial covers fine-tuning BERT for sentiment analysis using Hugging Face Transformers. Learn to prepare data, set up environment, train and evaluate the model, and make predictions.
A space on Hugging Face showcasing the LLM-Model-VRAM-Calculator, a tool designed to calculate the required VRAM for a specific machine learning model.
Learn how to build an open LLM app using Hermes 2 Pro, a powerful LLM based on Meta's Llama 3 architecture. This tutorial explains how to deploy Hermes 2 Pro locally, create a function to track flight status using FlightAware API, and integrate it with the LLM.
