Run 30,000+ LoRAs on Hugging Face with Replicate
We've partnered with Hugging Face to bring Replicate inference to their platform.
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Run MiniMax Speech-02 models with an API
MiniMax's Speech-02 models give you high-quality text-to-speech with voice cloning, emotional expression, and multilingual support.
Easel AI is now on Replicate
Advanced face swap and AI avatars from Easel AI are now on Replicate.
Stylized video with Wan2.1
One of the most fun ways to use Wan2.1 is video style transfer. Learn how here.
Creative roundup: avatars, lightsabers, and LoRA tricks
We take a quick look at the latest creative models, experiments, and community projects.
Wan2.1: generate videos with an API
Wan2.1 is the most capable open-source video generation model, producing coherent and high-quality outputs. Learn how to run it in the cloud with a single line of code.
Wan2.1 parameter sweep
We've been playing with Alibaba's WAN2.1 text-to-video model lately. What happens when you tweak those mysterious parameters? Let's find out.
You can now fine-tune open-source video models
Train your own versions of Tencent's HunyuanVideo for style, motion, and characters on Replicate.
Generate short videos with the Replicate playground
Create AI videos with a convenient workflow.
AI video is having its Stable Diffusion moment
There are lots of models that are as good as OpenAI's Sora now.
FLUX fine-tunes are now fast
We've made running fine-tunes on Replicate much faster, and the optimizations are open-source.
FLUX.1 Tools – Control and steerability for FLUX
A new set of image generation capabilities for FLUX models, including inpainting, outpainting, canny edge detection, and depth maps.
Extending the Context Length to 1M Tokens!
API Documentation (Chinese) HuggingFace Demo ModelScope Demo Introduction After the release of Qwen2.5, we heard the community’s demand for processing longer contexts. In recent months, we have made many optimizations for the model capabilities and inference performance of extremely long context. Today, we are proud to introduce the new Qwen2.5-Turbo version, which features: Longer Context Support: We have extended the model’s context length from 128k to 1M, which is approximately 1 million English words or 1.
FLUX is fast and it's open source
FLUX is now much faster on Replicate, and we’ve made our optimizations open-source so you can see exactly how they work and build upon them.
Qwen2.5: A Party of Foundation Models!
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction In the past three months since Qwen2’s release, numerous developers have built new models on the Qwen2 language models, providing us with valuable feedback. During this period, we have focused on creating smarter and more knowledgeable language models. Today, we are excited to introduce the latest addition to the Qwen family: Qwen2.5. We are announcing what might be the largest opensource release in history!
Qwen2.5-LLM: Extending the boundary of LLMs
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction In this blog, we delve into the details of our latest Qwen2.5 series language models. We have developed a range of decoder-only dense models, with seven of them open-sourced, spanning from 0.5B to 72B parameters. Our research indicates a significant interest among users in models within the 10-30B range for production use, as well as 3B models for mobile applications. To meet these demands, we are open-sourcing Qwen2.
Reduce hallucinations with Bespoke-Minicheck
Bespoke-Minicheck is a new grounded factuality checking model developed by Bespoke Labs that is now available in Ollama. It can fact-check responses generated by other models to detect and reduce hallucinations.
Qwen2-Audio: Chat with Your Voice!
DEMO PAPER GITHUB HUGGING FACE MODELSCOPE DISCORD To achieve the objective of building an AGI system, the model should be capable of understanding information from different modalities. Thanks to the rapid development of large language models, LLMs are now capable of understanding language and reasoning. Previously we have taken a step forward to extend our LLM, i.e., Qwen, to more modalities, including vision and audio, and built Qwen-VL and Qwen-Audio. Today, we release Qwen2-Audio, the next version of Qwen-Audio, which is capable of accepting audio and text inputs and generating text outputs.
Hello Qwen2
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction After months of efforts, we are pleased to announce the evolution from Qwen1.5 to Qwen2. This time, we bring to you: Pretrained and instruction-tuned models of 5 sizes, including Qwen2-0.5B, Qwen2-1.5B, Qwen2-7B, Qwen2-57B-A14B, and Qwen2-72B; Having been trained on data in 27 additional languages besides English and Chinese; State-of-the-art performance in a large number of benchmark evaluations; Significantly improved performance in coding and mathematics; Extended context length support up to 128K tokens with Qwen2-7B-Instruct and Qwen2-72B-Instruct.
Generalizing an LLM from 8k to 1M Context using Qwen-Agent
We’ve created an agent using Qwen2 models with an 8k context size to understand documents with 1M tokens, surpassing RAG and native long-context models. This agent was also used to generate data for training new long-context Qwen models.