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The interface displays model metadata (parameter count, training data, performance benchmarks), dataset statistics (size, languages, domains), and compatibility information. Selection is context-aware, suggesting compatible models and datasets based on training objective and available resources.","intents":["I want to find a suitable base model for fine-tuning without manually browsing HuggingFace Hub","I need to discover datasets that match my training objective and language requirements","I want to understand model and dataset characteristics before committing to a training run"],"best_for":["practitioners exploring available models and datasets","teams standardizing on specific model families","researchers comparing baseline models for experiments"],"limitations":["Catalog is limited to models and datasets available on HuggingFace Hub — custom or private resources require manual entry","Metadata may be incomplete or outdated for less popular models","No real-time performance benchmarking — comparisons are based on published results"],"requires":["Internet connection for HuggingFace Hub API access","HuggingFace account (optional, for accessing private models)"],"input_types":["search queries (text)","filter selections (model type, dataset language, size)"],"output_types":["model listings with metadata","dataset listings with statistics","compatibility recommendations"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-huggingfacetb--smol-training-playbook__cap_6","uri":"capability://automation.workflow.training.execution.workflow.orchestration","name":"training-execution-workflow-orchestration","description":"Orchestrates the complete training workflow from configuration through script generation and execution guidance, managing state and dependencies across steps. 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Integration points include HuggingFace Hub APIs for model/dataset discovery and external execution environments for script running.","intents":["I want a guided workflow that walks me through training setup from start to finish","I need to save and reuse training configurations across multiple runs","I want to compare results from different configurations systematically"],"best_for":["teams establishing standardized training workflows","practitioners managing multiple training experiments","organizations automating training pipeline setup"],"limitations":["Workflow is linear and does not support branching or conditional logic — complex multi-stage training requires manual orchestration","State persistence is limited to browser storage or HuggingFace Spaces — no integration with external experiment tracking systems","Execution monitoring is not built-in — users must check training progress in external environments"],"requires":["Web browser with session storage support","HuggingFace Spaces account (for saving configurations)","External Python environment for script execution"],"input_types":["user selections across workflow steps","configuration modifications"],"output_types":["training script","configuration file","documentation","resource estimates"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":25,"verified":false,"data_access_risk":"high","permissions":["Web browser with JavaScript enabled","HuggingFace Spaces account (optional, for saving configurations)","Python 3.8+ and PyTorch/TensorFlow installed locally to execute generated scripts","HuggingFace Transformers library (version 4.20+)","PyTorch or TensorFlow (matching template requirements)","Access to HuggingFace model hub or local model files","Model size information (parameter count or model identifier)","Dataset size (number of examples or total tokens)","Target hardware specification (GPU type, VRAM)","Constraint rule definitions (embedded in application)"],"failure_modes":["Limited to predefined hyperparameter ranges and model architectures — custom architectures require manual script editing","Estimates are approximate and may not account for hardware-specific optimizations or distributed training overhead","No real-time training execution or monitoring — generates scripts for external execution","Templates are fixed — custom training objectives or loss functions require manual script modification","Generated scripts assume standard HuggingFace Transformers API — incompatible with custom model implementations","No dependency version pinning — generated scripts may fail if environment has incompatible library versions","Estimates are based on average hardware performance — actual results vary by GPU model, driver version, and system configuration","Does not account for data loading bottlenecks, validation overhead, or checkpointing frequency","Cost estimates assume standard cloud pricing and may not reflect reserved instances or custom pricing agreements","Validation rules are heuristic-based and may reject valid but unconventional configurations","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.24,"ecosystem":0.48000000000000004,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.766Z","last_scraped_at":"2026-05-03T14:22:48.012Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=huggingfacetb--smol-training-playbook","compare_url":"https://unfragile.ai/compare?artifact=huggingfacetb--smol-training-playbook"}},"signature":"GnbDN4QlUx4Ledbb6pNF3u5om/3VtktVCOzK5Kp+1BRDHHRrTTipy2Xxk6RufQZdaEC0dGCOIMP8u1sHor0bDg==","signedAt":"2026-06-20T14:10:18.696Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/huggingfacetb--smol-training-playbook","artifact":"https://unfragile.ai/huggingfacetb--smol-training-playbook","verify":"https://unfragile.ai/api/v1/verify?slug=huggingfacetb--smol-training-playbook","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}