Transformers
Named by 31 kept items in this workspace.
27 items name it under frameworks and tools and 4 under classification.technologies.
The items that name it 31
Hugging Face library with day-0 support for Mistral Large 4 via AutoModelForMultimodalLM and AutoProcessor; supports distributed inference with tensor and expert parallelism.
Library that loads Nanbeige4.3-33B with trust_remote_code.
Library whose models are tested; loads models with from_pretrained and runs its own modeling code on Trainium.
Native support for all three Granite Speech models.
Hugging Face model definition library (v5). Loads models on TPU with device_map="tpu".
Hugging Face library for running models on a Mac with PyTorch.
Hugging Face library that runs text generation and training on Neuron via device_map=neuron and DistributedConfig.
Library used to load the model via pipeline (image-text-to-text) or AutoModelForCausalLM
Baseline compiled implementation for full Llama-3.1-8B decode
Native Beam implementation (>=5.20.1) with pipeline, chat template, parse_response and DistributedConfig for expert parallelism
Hugging Face library providing MuseSparkForConditionalGeneration and MuseSparkProcessor; DistributedConfig sets tensor, expert and FSDP parallelism.
Provides the Qwen3-VL text encoder
Used to serve the model efficiently
Required for GPU inference in reproduction.
Library supporting Nemotron 3 Diarization on day 0
Hugging Face library providing a foundation for model definition; now loads and runs GGUF quantized checkpoints, reusing ggml kernels via the kernels library and with an optimized generate loop for local inference.
Inference library accompanying open-weight model releases
library that depends on tokenizers and is planned to receive its performance improvements after the release candidates stabilize
Hugging Face library used to load the tokenizer and model and run inference (thinking mode, non-thinking mode, low-effort thinking, tool calling) for Granite 4.2.
Backend library Soup trains against; a recipe can train a different result on this backend than on MLX
Library referenced for self-hosting GLM-5 using its open chat template to control turn-level thinking.
Hugging Face library; pipeline (image-text-to-text) and AutoModelForMultimodalLM/AutoProcessor to load and run the model
Library used to load google/embeddinggemma-2 via pipeline (feature-extraction) or AutoProcessor/AutoModel
Library used to load and run tencent/Hy4-preview via pipeline or direct model/tokenizer loading
Library used to load and run DeepSeek-V4.1-Flash via pipeline or AutoModelForCausalLM
Library to load and run MiMo-V2.6-Pro-RL via a pipeline or AutoModelForCausalLM
Python library used to load and run MiMo-V2.6-Flash-RL via pipeline or AutoModelForCausalLM
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AI
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