Hugging Face Transformers

E99320
Python library machine learning framework natural language processing toolkit open-source library software library

Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.

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Observed surface forms (2)

Surface form Occurrences
AutoModel 1
AutoTokenizer 1

Statements (92)

Predicate Object
instanceOf Python library ⓘ
machine learning framework ⓘ
natural language processing toolkit ⓘ
open-source library ⓘ
software library ⓘ
compatibleWith Hugging Face Accelerate ⓘ
Hugging Face Datasets ⓘ
JAX ⓘ
PyTorch ⓘ
TensorFlow NERFINISHED ⓘ
developer Hugging Face ⓘ
documentation https://huggingface.co/docs/transformers ⓘ
domain computer vision ⓘ
natural language processing ⓘ
speech processing ⓘ
ecosystemPartOf Hugging Face ⓘ
surface form: Hugging Face Hub

Hugging Face ecosystem ⓘ
hasFeature JAX integration ⓘ
ONNX export ⓘ
PyTorch integration ⓘ
TensorFlow integration ⓘ
distributed training support ⓘ
fine-tuning utilities ⓘ
integration with Hugging Face Hub ⓘ
mixed precision training ⓘ
model configuration management ⓘ
model pruning utilities ⓘ
pipeline API ⓘ
pretrained model loading ⓘ
quantization support ⓘ
task-specific heads ⓘ
tokenizer abstraction ⓘ
trainer API ⓘ
license Apache License 2.0 NERFINISHED ⓘ
programmingLanguage JavaScript ⓘ
Python ⓘ
Rust ⓘ
repository https://github.com/huggingface/transformers ⓘ
supportsModelType ALBERT ⓘ
AutoConfig ⓘ
Hugging Face Transformers self-linksurface differs ⓘ
surface form: AutoModel

Hugging Face Transformers self-linksurface differs ⓘ
surface form: AutoTokenizer

BART ⓘ
Transformer ⓘ
surface form: BERT

BigBird ⓘ
Bloom ⓘ
CLIP ⓘ
DeBERTa ⓘ
DeiT ⓘ
DistilBERT ⓘ
EncoderDecoderModel ⓘ
Falcon ⓘ
GPT-2 ⓘ
GPT-Neo ⓘ
HuBERT ⓘ
LLaMA ⓘ
LayoutLM ⓘ
Longformer ⓘ
OPT ⓘ
Pegasus ⓘ
RoBERTa ⓘ
API for Whisper ⓘ
surface form: Speech2Text

Swin Transformer ⓘ
T5 ⓘ
ViT ⓘ
VisionEncoderDecoderModel ⓘ
Wav2Vec2 ⓘ
Whisper ⓘ
XLM-R ⓘ
XLNet ⓘ
mBART ⓘ
supportsTask audio classification ⓘ
automatic speech recognition ⓘ
conversational AI ⓘ
embedding generation ⓘ
feature extraction ⓘ
image classification ⓘ
language modeling ⓘ
multiple choice classification ⓘ
question answering ⓘ
summarization ⓘ
text classification ⓘ
text generation ⓘ
text-to-text generation ⓘ
token classification ⓘ
tokenization ⓘ
translation ⓘ
vision-language modeling ⓘ
zero-shot classification ⓘ
usedFor production machine learning systems ⓘ
prototyping NLP models ⓘ
research ⓘ

Referenced by (3)

Full triples — surface form annotated when it differs from this entity's canonical label.

GPT-2 → openSourceImplementation → Hugging Face Transformers ⓘ
Hugging Face Transformers → supportsModelType → Hugging Face Transformers self-linksurface differs ⓘ
this entity surface form: AutoModel
Hugging Face Transformers → supportsModelType → Hugging Face Transformers self-linksurface differs ⓘ
this entity surface form: AutoTokenizer