Neotask searches models, papers, datasets, and Spaces on the Hugging Face Hub - your AI research and deployment workflow in one conversation.
Find the right model for any task using semantic search instead of memorizing exact names
Run and manage training or inference jobs directly from your workflow
Research papers, explore Spaces demos, and browse documentation without leaving chat
What You Can Do
Neotask brings the entire Hugging Face Hub into your workflow. Whether you are evaluating models, reading papers, or running compute jobs, everything happens in natural language.
Model Discovery
Search for models by task, architecture, size, or capability using semantic search. Describe the problem you are solving and get back the most relevant models - no need to memorize naming conventions.
Dataset Research
Find datasets by topic, format, or size. Neotask helps you evaluate dataset suitability before committing to a training run.
Paper Exploration
Search through Hugging Face's paper collection semantically. Describe a technique, problem, or approach and surface the most relevant publications.
Spaces Demos
Find interactive demos on Hugging Face Spaces to evaluate models before downloading them. See how they perform on real inputs.
Job Management
Run and manage training or inference jobs. Check status, review outputs, and iterate on your ML workflows without switching interfaces.
Documentation Search
Search Hugging Face docs semantically for answers about transformers, diffusers, datasets, or any other library.
Every action runs autonomously or requires your approval - you decide.
Try Asking
"Find the best open-source code generation models under 7B parameters"
"Search for recent papers on mixture-of-experts architectures"
"What datasets are available for medical named entity recognition in English?"
"Show me Spaces that demo real-time image generation"
"Start an inference job using this model on my test dataset"
"What does the transformers documentation say about flash attention?"
"Compare the top 3 text-to-SQL models by benchmark performance"
Pro Tips
Use semantic search to discover models you did not know existed - describe the problem, not the model name.
Combine model search with paper search to find both the implementation and the research behind it.
Check Spaces demos before downloading large models to verify they meet your needs.
Repository details include model cards with licensing and limitation information - always check before production use.
For ML pipeline selection, describe your constraints (hardware, latency, accuracy) and let Neotask recommend the best fit.
Multiple workspaces and capacity for larger teams.
Works Well With
Google Business Profile - Connect Google Business Profile with Hugging Face via Neotask to automate AI review management, generate intelligent rev...
Notion - Connect Hugging Face and Notion with Neotask to automate AI model documentation, track ML experiments, and build a searc...
More AI & ML Integrations
Arize Phoenix - Neotask automates your LLM observability pipeline through Arize Phoenix - monitoring traces, managing prompts, and running experiments so your AI systems stay reliable.
Label Studio - Manage data labeling projects and annotations through conversation - Neotask uses AI agents to operate your Label Studio annotation infrastructure.
Anthropic - Call Claude models, manage prompts, and monitor usage - Neotask orchestrates your Anthropic API.
Scholar Gateway - Neotask connects your research workflows to Wiley's Scholar Gateway - running semantic search across peer-reviewed scientific literature to ground your work in authoritative sources.
Stability AI - Generate, edit, and transform images with Stable Diffusion - Neotask runs your Stability AI workflows.
Cohere - Generate text, rerank results, and build enterprise search - Neotask puts Cohere's NLP suite to work.