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Welcome to Inference Providers on the Hub π₯
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Saugat Kafley
Saugatkafley
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AI, Machine Learning, Deep Learning
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Welcome to Inference Providers on the Hub π₯
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Runway Gen-3 Alpha: The Style and Coherence Champion
Runway's latest video generation model, Gen-3 Alpha, is something special. It ranks #3 overall on our text-to-video human preference benchmark, but in terms of style and coherence, it outperforms even OpenAI Sora.
However, it struggles with alignment, making it less predictable for controlled outputs.
We've released a new dataset with human evaluations of Runway Gen-3 Alpha: Rapidata's text-2-video human preferences dataset. If you're working on video generation and want to see how your model compares to the biggest players, we can benchmark it for you.
π DM us if youβre interested!
Dataset: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-runway-alpha
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Saugatkafley's activity
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Runway Gen-3 Alpha: The Style and Coherence Champion
Runway's latest video generation model, Gen-3 Alpha, is something special. It ranks #3 overall on our text-to-video human preference benchmark, but in terms of style and coherence, it outperforms even OpenAI Sora.
However, it struggles with alignment, making it less predictable for controlled outputs.
We've released a new dataset with human evaluations of Runway Gen-3 Alpha: Rapidata's text-2-video human preferences dataset. If you're working on video generation and want to see how your model compares to the biggest players, we can benchmark it for you.
π DM us if youβre interested!
Dataset: Rapidata/text-2-video-human-preferences-runway-alpha
Runway's latest video generation model, Gen-3 Alpha, is something special. It ranks #3 overall on our text-to-video human preference benchmark, but in terms of style and coherence, it outperforms even OpenAI Sora.
However, it struggles with alignment, making it less predictable for controlled outputs.
We've released a new dataset with human evaluations of Runway Gen-3 Alpha: Rapidata's text-2-video human preferences dataset. If you're working on video generation and want to see how your model compares to the biggest players, we can benchmark it for you.
π DM us if youβre interested!
Dataset: Rapidata/text-2-video-human-preferences-runway-alpha
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Happy New Year 2025 π€
For the Huggingface community.
For the Huggingface community.
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I've been working on a Space to make it super easy to create notebooks and help users quickly understand and manipulate their data!
With just a few clicks automatically generate notebooks for:
π Exploratory Data Analysis
π§ Text Embeddings
π€ Retrieval-Augmented Generation (RAG)
β¨ Automatic training is coming soon!
Check it out here asoria/auto-notebook-creator
Appreciate any feedback to improve this tool π€
With just a few clicks automatically generate notebooks for:
π Exploratory Data Analysis
π§ Text Embeddings
π€ Retrieval-Augmented Generation (RAG)
β¨ Automatic training is coming soon!
Check it out here asoria/auto-notebook-creator
Appreciate any feedback to improve this tool π€
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I am training a controlnet model for Flux. And some of my experiences:
Checkpoint-10000:
https://x.com/kadirnar_ai/status/1829831750471606668
Checkpoint-12000:
https://x.com/kadirnar_ai/status/1829889524962640001
Checkpoint-14000:
https://x.com/kadirnar_ai/status/1829989622878744711
Checkpoint (16000-18000):
https://x.com/kadirnar_ai/status/1830179551407665654
Dataset: kadirnar/fluxdev_controlnet_16k
GPU: 1xA100(80GB)
GPU Hours: 65
Checkpoint-10000:
https://x.com/kadirnar_ai/status/1829831750471606668
Checkpoint-12000:
https://x.com/kadirnar_ai/status/1829889524962640001
Checkpoint-14000:
https://x.com/kadirnar_ai/status/1829989622878744711
Checkpoint (16000-18000):
https://x.com/kadirnar_ai/status/1830179551407665654
Dataset: kadirnar/fluxdev_controlnet_16k
GPU: 1xA100(80GB)
GPU Hours: 65
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π We will be generating a preference dataset for DPO/ORPO and cleaning it with AI feedback during our upcoming meetup!
In this session, we'll walk you through the essentials of building a distilabel pipeline by exploring two key use cases: cleaning an existing dataset and generating a preference dataset for DPO/ORPO. Youβll also learn how to make the most of AI feedback, integrating Argilla to gather human feedback and improve the overall data quality.
This session is perfect for you
- if youβre getting started with distilabel or synthetic data
- if you want to learn how to use LLM inference endpoints for **free**
- if you want to discover new functionalities
- if you want to provide us with new feedback
Sign up here: https://lu.ma/dt0c7jru
In this session, we'll walk you through the essentials of building a distilabel pipeline by exploring two key use cases: cleaning an existing dataset and generating a preference dataset for DPO/ORPO. Youβll also learn how to make the most of AI feedback, integrating Argilla to gather human feedback and improve the overall data quality.
This session is perfect for you
- if youβre getting started with distilabel or synthetic data
- if you want to learn how to use LLM inference endpoints for **free**
- if you want to discover new functionalities
- if you want to provide us with new feedback
Sign up here: https://lu.ma/dt0c7jru
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π Calling all Hugging Face users! We want to hear from YOU!
What feature or improvement would make the biggest impact on Hugging Face?
Whether it's the Hub, better documentation, new integrations, or something completely different β we're all ears!
Your feedback shapes the future of Hugging Face. Drop your ideas in the comments below! π
What feature or improvement would make the biggest impact on Hugging Face?
Whether it's the Hub, better documentation, new integrations, or something completely different β we're all ears!
Your feedback shapes the future of Hugging Face. Drop your ideas in the comments below! π
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Is your summer reading list still empty? Curious if an LLM can generate a book blurb you'd enjoy and help build a KTO preference dataset at the same time?
A demo using Hugging Face Spaces and Gradio to collect LLM output preferences: davanstrien/would-you-read-it
A demo using Hugging Face Spaces and Gradio to collect LLM output preferences: davanstrien/would-you-read-it
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#8 opened 7 months ago
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Saugatkafley
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