Buckets:
transformers
Public API of @huggingface/transformers. Everything re-exported from
this file is considered stable — other imports are internal and may change.
Start here
pipeline()— the one-call entry point for every task.- Environment —
envfields andLogLevelenum.
Model loading
- Pipelines — task-specific pipeline classes (
TextGenerationPipeline, etc.). - Models —
AutoModel*classes (one per task). - Tokenizers —
AutoTokenizer, chat templates,Message. - Processors —
AutoProcessor,AutoImageProcessor,AutoFeatureExtractor. - Configs —
AutoConfig/PretrainedConfig.
Generation
- Generation config — sampling and beam-search parameters.
- Generation parameters — full shape of
generate()arguments. - Logits processors — modify next-token probabilities.
- Stopping criteria — control when generation halts.
- Streamers — receive tokens as they're produced.
Data types and I/O
- Tensors —
Tensor, shape ops, math, I/O. - Images —
RawImage,load_image(). - Audio —
RawAudio,load_audio(). - Video —
RawVideo,RawVideoFrame,load_video()(experimental).
Utilities
- Hub options — shared
from_pretrained()option shapes. - Maths —
softmax,cos_sim, typed-array helpers. - Model registry — inspect or clear the model cache.
- Random — seedable MT19937 PRNG matching Python's
random.
Type Definitions
DeviceType
Type: keyof typeof DEVICE_TYPES
DataType
Type: keyof typeof DATA_TYPES
Xet Storage Details
- Size:
- 1.96 kB
- Xet hash:
- 5dd5ee6e39f10f1427299ead58234615e9404b618a1dbb7dcf2d98495022c7a0
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.