Transformers
Transformers is a model architecture that uses attention mechanisms as described in the foundational "Attention is All You Need" paper and serves as a baseline for comparing alternative architectures like Mamba. The Hugging Face Transformers library has become a standardized model definition layer supporting over 300 model architectures with approximately 3 new architectures added weekly, integrating with training frameworks and inference engines to enable seamless interoperability across the ML ecosystem. Recently, the library has expanded to support computer vision models from timm, added constrained beam search for controlled text generation, integrated with quantization and inference optimization tools, and begun tracking carbon emissions from model training.
Updated 3 August 2026
Specifications
No specifications recorded yet.
Latest developments
Everything a Senior Engineer Needs to Know About What's Inside an LLM
TLDR Dev · 1 month ago ·
41
PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters
Hugging Face Blog · 1 month ago ·
34
Is it agentic enough? Benchmarking open models on your own tooling
Hugging Face Blog · 1 month ago ·
1
PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers Backend
Hugging Face Blog · 2 months ago ·
45
The PR you would have opened yourself
Hugging Face Blog · 3 months ago ·
29
The Transformers Library: standardizing model definitions
Hugging Face Blog · 1 year ago ·
47
SmolVLM2: Bringing Video Understanding to Every Device
Hugging Face Blog · 1 year ago ·
18
Timm ❤️ Transformers: Use any timm model with transformers
Hugging Face Blog · 1 year ago ·
12
2026
- Everything a Senior Engineer Needs to Know About What's Inside an LLM
- PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters
- Is it agentic enough? Benchmarking open models on your own tooling
- PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers Backend
- The PR you would have opened yourself
2025
- The Transformers Library: standardizing model definitions
- SmolVLM2: Bringing Video Understanding to Every Device
- Timm ❤️ Transformers: Use any timm model with transformers
2024
2023
Mistral AI releases Mixtral 8x7B, an open-weights mixture-of-experts language model Model release
2022
- Deploying TensorFlow Vision Models in Hugging Face with TF Serving
- Accelerated Inference with Optimum and Transformers Pipelines
- CO2 Emissions and the 🤗 Hub: Leading the Charge
- ~Don't~ Repeat Yourself
- Guiding Text Generation with Constrained Beam Search in 🤗 Transformers
- Making automatic speech recognition work on large files with Wav2Vec2 in 🤗 Transformers
- Boosting Wav2Vec2 with n-grams in 🤗 Transformers
2019
Relationships
Products & technology
- Hugging Face develops this model · 5 sources
- Integrated with TensorFlow · 1 source
- Integrated with Wav2Vec2 · 1 source
- Integrated with pyctcdecode · 1 source
- Integrated with timm · 1 source
- Integrated with Axolotl · 1 source
- Integrated with vLLM · 1 source
- Integrated with llama.cpp · 1 source
- Optimum integrated with this model · 1 source
- Wav2Vec2 integrated with this model · 1 source
- codecarbon integrated with this model · 1 source
- PaddleOCR integrated with this model · 1 source