Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running…
Use when adding a new model or pipeline to diffusers, setting up file structure for a new model, converting a pipeline to modular format, or converting weights for a new version…
Use when fine-tuning LLMs with TRL — SFT, DPO, PPO, GRPO, reward modeling, RLHF. Triggers: SFT, DPO, GRPO, fine-tune, RLHF, reward model, TRL.
Train or fine-tune TRL language models on Hugging Face Jobs, including SFT, DPO, GRPO, and GGUF export.
Hugging Face Transformers provides 400,000+ pretrained models for NLP, computer vision, audio, and multimodal tasks with a unified API across PyTorch, TensorFlow, and JAX for…
Use when debugging or verifying numerical parity between pipeline implementations (e.g., research repo vs diffusers, standard vs modular).
Use the Hugging Face Hub CLI (`hf`) to download, upload, and manage models, datasets, and Spaces.
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing repositories, models, datasets, and Spaces on the Hugging Face Hub.
Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure.
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running…
Turn successful traces into reusable skills, then benchmark those skills across models before you trust them in production.