Tools tagged with "Hugging Face integration"

Nemotron is NVIDIA's family of AI models for developers building agents that reason, write code and call tools. You can run models locally for private, offline work or deploy them on your own servers. NVIDIA publishes model weights, training data and recipes so teams can inspect and adapt the models for their applications.

Mistral Small and Large are downloadable language models for developers building chat, reasoning and tool-using applications on their own infrastructure. Capabilities and hardware requirements depend on the release. Mistral Small 3.1 adds image understanding to text generation, while Mistral Large 2 is a larger text model.

GLM-4.5 is an open-source language model for developers building AI agents and coding tools on their own servers. It combines reasoning with tool calling and offers a choice between thinking mode for complex tasks and non-thinking mode for direct responses. The MIT license permits commercial use and modification.

lm-evaluation-harness lets researchers and model developers compare language models using shared academic benchmarks and public prompts. It runs evaluations against local models and benchmarks, or sends requests to a hosted model API. EleutherAI's Python framework is open source under the MIT license and powers Hugging Face's Open LLM Leaderboard.

Hallo turns a single portrait and a speech recording into an animated talking video on your own hardware. It's a local AI tool for creators working with talking portraits and researchers who want access to both generation and training code. The Python code uses the MIT license; required pretrained models and dependencies have their own terms.

Marqo Open Source is a self-hosted search engine for developers building semantic document search, image search, or retrieval for AI applications. It handles embedding generation alongside storage and retrieval, so applications can submit documents without maintaining a separate embedding service. The open-source project is deprecated and no longer receives updates.

Deforum is a free Stable Diffusion tool for artists and developers who want to generate images and animations on their own hardware. The project is no longer maintained. Its code uses MIT, while downloaded Stable Diffusion models retain their own weight licenses. Its Python script and Jupyter notebook support local generation, while Google Colab and Replicate offer cloud execution.

Falcon-H1 is a family of language models from the Technology Innovation Institute for developers building local AI applications or serving models on their own hardware. Its hybrid design combines attention with Mamba2 state space models to reduce memory use and speed up inference. Model sizes cover smaller devices and larger server deployments.

CosyVoice is a local text-to-speech system for developers and researchers who want to generate speech in a reference speaker's voice, including in another language. Its zero-shot voice cloning doesn't require training a separate model for each speaker. You can run it on your own hardware or deploy it as a self-hosted service.

MiniCPM-V is a family of local vision-language models for developers building apps that interpret images and video on their own hardware. It supports iOS, Android and HarmonyOS, as well as Mac deployment and server inference. The current repository states that MiniCPM-o/V code and model weights use Apache 2.0.

Kolors is a text-to-image model for people who want to generate photorealistic images on their own hardware, including work with Chinese prompts and Chinese cultural content. Developed by Kuaishou, it understands prompts in Chinese and English and can render text in both languages within generated images.

Kimi K2 is Moonshot AI's language model series for developers building coding assistants and AI agents, and researchers who want a foundation model to customize. You can run its checkpoints on your own infrastructure or use Moonshot's hosted API. Local inference runs on your hardware; the hosted API sends requests to Moonshot's service.

PaliGemma is a family of downloadable vision-language models for developers and researchers building applications that work with images and text. It combines SigLIP's image processing with Gemma's language capabilities to answer questions about visual content. Its main appeal is task-specific fine-tuning: you can adapt a base model to your own image data and intended use.

PixArt-Sigma is a text-to-image diffusion model that supports generation at 2K and 4K resolutions on your own machine or server. It's aimed at developers and researchers who want pretrained models they can run themselves, along with code for training and adapting them. The Python code is open source under Apache 2.0.

EXAONE 4.0 is a family of language models from LG AI Research that combines general language tasks and complex problem solving in the same model. It's aimed at developers building multilingual AI applications, including on-device apps and agents that use tools. It supports English, Korean and Spanish.

StarCoder2 is a family of code generation models for developers who want to run code completion on their own hardware or adapt a model to their code. It predicts code continuations rather than following conversational instructions, so it's suited to completion workflows rather than a chat-based coding assistant.

DeepSeek-Coder is a family of code language models for developers who want downloadable models for their own coding tools. It generates code, completes existing code, and fills gaps within a file using the surrounding context. DeepSeek also offers a hosted chat interface; the downloadable weights are separate from that service.

Phi-4 is Microsoft's small language model for complex reasoning and math problem solving. It's for developers building generative AI applications who want to run a model on their own hardware, rather than depend on a cloud connection. The original Phi-4 has 14 billion parameters and uses the MIT license; hardware needs depend on the chosen model and precision.

Granite is IBM's family of open-source AI models for developers and businesses that want to run and customize AI on their own hardware or servers. The language-model repository listed here is archived and no longer maintained. The broader family includes models for language, speech, document understanding and forecasting, released under Apache 2.0 for research and commercial use.

Yi is a family of open-weight language models from 01.AI for developers, researchers, and businesses that want to run English and Chinese models on their own hardware. It includes models for conversation and base models for fine-tuning, with license terms that depend on the release. Yi-1.5 code and weights use Apache 2.0; the original Yi releases have separate community terms.

MiniMax-M1 is an open-source reasoning model for developers building agents or working on complex software and mathematical problems. Its million-token context window makes it a candidate for tasks with long inputs that also need extended reasoning. You can serve the model on your own infrastructure through vLLM or use it through Transformers.

InternLM is a family of downloadable language models for developers and researchers building their own AI applications. It includes models for general conversation, complex reasoning and coding, with separate base and chat variants for customization or use in an assistant.

HiDream-I1 is an open-source text-to-image model for people who want to generate images on their own hardware or build image generation into a Python application. It uses MIT licensing and supports local inference through CUDA, making it an option for developers and creators with NVIDIA GPU hardware.

JoyCaption is an open-weight image captioning model for people preparing datasets to train or fine-tune diffusion models. It runs on your own GPU and covers both SFW and NSFW images, including photography, anime, digital art and furry artwork. Automated captions reduce the need to write descriptions by hand or find images that already have usable text.

Parler-TTS generates speech locally, with text descriptions that control how the voice sounds. It's a Python library for developers building speech into applications and researchers who want to train or adapt a TTS model. The library uses the Apache 2.0 license and can run on CPU or CUDA GPUs, with support for Apple Silicon.

Spark-TTS is a local text-to-speech system that can copy a voice from reference audio or create a synthetic speaker with adjustable vocal traits. It's for developers and researchers building speech applications, including personalized narration, assistive technology, and language research. The Python and PyTorch code is open source under Apache 2.0.

Grounding DINO finds objects in images using category names or descriptive phrases you supply. It's a local AI model for developers and computer vision researchers who need detection beyond a fixed set of labels, including people building dataset annotation tools.

OpenCLIP is a Python and PyTorch library for developers and researchers who want to match images with text on their own hardware. It implements OpenAI's CLIP approach: images and descriptions become numerical representations that the model can compare. This supports image search and zero-shot classification, where text labels define the categories without a separate classifier trained for each task.

Intel IPEX-LLM is a library for developers running or fine-tuning models on Intel hardware. The project is archived and no longer maintained. Intel reports known security issues and no longer accepts patches or provides updates. The code is open source under Apache 2.0.

Text Generation Inference (TGI) is a self-hosted LLM server for developers and teams serving models through an API on their own hardware. The repository is archived; its README describes maintenance mode and recommends other inference engines for new deployments. Its focus is handling concurrent generation requests and making efficient use of GPU memory.

OmniGen is a local AI image generation model that handles text prompts, reference images, and image editing within one model. It's for creators who want to reuse subjects across images and developers building image tools on their own hardware. The code is open source under the MIT license.

Janus-Pro is a multimodal AI model from DeepSeek that answers questions about images and creates pictures from text prompts. It runs on your own hardware and suits developers and researchers who want both capabilities in one model. A local Gradio demo provides a browser interface, while Hugging Face hosts a separate online demo.

Lumina-Image 2.0 is a local AI image generation framework for developers, researchers and people who want to generate images from text on their own hardware. It provides downloadable checkpoints, generation code and tools for adapting the model to your own image collections. The code uses the Apache 2.0 license.

Orpheus TTS is an open-source text-to-speech system for developers building voice applications or adapting speech models to their own recordings. It runs locally and uses a Llama backbone to generate speech with control over emotion and intonation. The code uses the Apache 2.0 license.

Bark is Suno's local text-to-audio model for developers and researchers who want to generate speech alongside other sounds. It can produce laughter, crying, music and background noise within its output. Its generative approach suits audio experiments, though it can depart from the supplied script and doesn't guarantee clean, studio-quality speech.

Dia is the original text-to-speech model from Nari Labs that generates a two-speaker conversation from a written script in one pass. It's for researchers and developers who want to generate English dialogue on their own hardware, with control over speaker voices and delivery. The code and model weights are available under Apache 2.0. Dia2 is a separately linked successor.