You can now fine-tune open-source video models
Train your own versions of Tencent's HunyuanVideo for style, motion, and characters on Replicate.
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Replicate
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Generate short videos with the Replicate playground
Create AI videos with a convenient workflow.
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Replicate
AI video is having its Stable Diffusion moment
There are lots of models that are as good as OpenAI's Sora now.
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Replicate
FLUX fine-tunes are now fast
We've made running fine-tunes on Replicate much faster, and the optimizations are open-source.
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Replicate
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.
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Replicate
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.
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Qwen
FLUX는 빠르고 오픈 소스입니다
FLUX는 이제 Replicate에서 훨씬 더 빠르며, 저희의 최적화 방식을 오픈소스로 공개하여 여러분이 그 작동 원리를 정확히 확인하고 이를 기반으로 발전시킬 수 있도록 했습니다.
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Replicate
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!
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Qwen
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.
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Qwen
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.
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Ollama