Hugging Face
🛠️ Developer ToolsfreemiumFeatured
★4.7
Open-source AI model hub and deployment platform
modelsopen-sourcedeployment
Try Hugging Face →Use Cases
- •Host and share open-source ML models with the community via the Model Hub
- •Fine-tune pre-trained transformer models for NLP tasks like text classification and NER
- •Deploy ML models as interactive web apps using Spaces with free GPU access via ZeroGPU
Integrations
PyTorchTensorFlowJAXLangChainAWS SageMakerGoogle Cloud Vertex AIGradioStreamlit
Pros
- +Largest open-source ML model repository with hundreds of thousands of community models
- +Free Inference API and ZeroGPU Spaces make ML accessible without owning hardware
- +Transformers library is the de facto standard for working with pre-trained models in Python
Cons
- -Free tier GPU quotas are limited and can have long queue wait times
- -Platform can be overwhelming for beginners due to the sheer volume of models and datasets
- -Inference API free tier has rate limits that are too restrictive for production use
Quick Start
1. Go to huggingface.co and create a free account
2. Browse the Model Hub to find a pre-trained model for your task (e.g., text generation, image classification)
3. Use the Inference API or click 'Use this model' to try it directly in the browser
4. For custom work, install the transformers library: pip install transformers
5. Load and run models in Python with just a few lines using the pipeline API
Pricing
Free: Unlimited public repos, 100GB private storage, community Inference credits, ZeroGPU access. Pro: $9/mo — 8x ZeroGPU quota, priority GPU access including H200, 100GB private storage. Team: $20/user/mo — 1TB storage, SSO, role-based permissions, audit logs. Enterprise: Custom pricing — dedicated infrastructure, SLA, private model hosting.