Course comparison
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Compare up to three published courses by skills, level, duration, prerequisites and certification requirements.
| Compare | Hugging Face for AI Engineers |
|---|---|
| Level | Intermediate |
| Duration | 18–26 study hours including labs |
| Format | Self-paced course |
| Access | Premium access |
| Skills | Transformers library, Tokenizers, Datasets, Hub, accelerate high level, AutoModel, AutoConfig, model architecture, config fields, checkpoint files, encode/decode, batch encoding, attention masks, padding/truncation, special tokens, pipeline, generation inputs, classification outputs, manual model invocation, load_dataset, mapping transforms, splits, streaming concept, dataset inspection, max_new_tokens, temperature, top-k, top-p, greedy decoding, sampling, model IDs, revision/version, cache, local model directories |
| Modules | 7 |
| Prerequisites | Transformers; PyTorch |
| Assessment | Course assessment |
| Certificate | Completion requirements apply |