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USA-NJ-MAYSVILLE Κατάλογοι Εταιρεία
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Εταιρικά Νέα :
- Hugging Face – The AI community building the future.
More than 50,000 organizations are using Hugging Face Ai2 Enterprise non-profit
- Welcome - Hugging Face
Welcome to Hugging Face Explorer App Builder Engineer Researcher HF Spaces The community AI apps directory Open source libraries The ultimate open source toolbox for AI Local Models Run models on your home computer Inference Playground Play with different models and providers
- Models - Hugging Face
lightx2v Wan2 1-T2V-14B-StepDistill-CfgDistill Text-to-Video • Updated 1 day ago • 44 nvidia GR00T-N1 5-3B
- Hugging Face - Learn
We’re on a journey to advance and democratize artificial intelligence through open source and open science
- huggingface (Hugging Face)
👋 Hi! We are on a mission to democratize good machine learning, one commit at a time If that sounds like something you should be doing, why don't you join us! For press enquiries, you can ️ contact our team here
- Tasks - Hugging Face
Hugging Face is the home for all Machine Learning tasks Here you can find what you need to get started with a task: demos, use cases, models, datasets, and more!
- Hugging Face – The AI community building the future.
We’re on a journey to advance and democratize artificial intelligence through open source and open science
- Hugging Face - Documentation
Python client to interact with the Hugging Face Hub Huggingface js JavaScript libraries for Hugging Face with built-in TS types Tasks Explore demos, models, and datasets for any ML tasks Dataset viewer API for metadata, stats, and content of HF Hub datasets Deployment Inference
- Introduction - Hugging Face LLM Course
This course will teach you about large language models (LLMs) and natural language processing (NLP) using libraries from the Hugging Face ecosystem — 🤗 Transformers, 🤗 Datasets, 🤗 Tokenizers, and 🤗 Accelerate — as well as the Hugging Face Hub
- Hugging Face Hub documentation
The Hugging Face Hub is a platform with over 1 7M models, 400k datasets, and 600k demos in which people can easily collaborate in their ML workflows The Hub works as a central place where anyone can share, explore, discover, and experiment with open-source Machine Learning
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