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Download upstreams/langflow/README.md from jyliuAI/diffusion_baseline: direct link, hf CLI and curl.
- Browser
- Download file 2.5 kB
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https://huggingface.co/jyliuAI/diffusion_baseline/resolve/main/upstreams/langflow/README.md
- Command line
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hf download hf://jyliuAI/diffusion_baseline/upstreams/langflow/README.md
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curl -L -o README.md https://huggingface.co/jyliuAI/diffusion_baseline/resolve/main/upstreams/langflow/README.md
2.5 kB
By Yuxin Chen*, Chumeng Liang*, Hangke Sui*, Ruihan Guo, Chaoran Cheng, Jiaxuan You, Ge Liu.
The first continuous diffusion language model that rivals discrete counterparts on standard language modeling benchmarks like LM1B and OpenWebText.
TODO
- Inference code
- PPL evaluation code
- OpenWebText checkpoint on HuggingFace
- LM1B checkpoint on HuggingFace
- Training code (after paper acceptance)
- All trainable checkpoints (after paper acceptance)
Quick Start
1. Install dependencies
conda create -n langflow python=3.12
conda activate langflow
# Install CUDA-enabled torch first (adjust cu124 to match your driver)
pip install torch --index-url https://download.pytorch.org/whl/cu124
pip install -r requirements.txt
2. Download the checkpoint
Download only the safetensors weights file from HuggingFace — no need to clone the HF repo:
# Using huggingface-hub CLI
hf download Continuous-Rivals-Discrete/langflow-owt model.safetensors --local-dir ./checkpoints
3. Run inference
python inference.py \
--checkpoint ./checkpoints/model.safetensors \
--num_samples 5 \
--batch_size 1 \
--num_steps 1024 \
--seq_length 1024 \
--seed 42 \
--output samples.txt
Citation
@article{chen2026langflow,
title={LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling},
author={Chen, Yuxin and Liang, Chumeng and Sui, Hangke and Guo, Ruihan and Cheng, Chaoran and You, Jiaxuan and Liu, Ge},
journal={arXiv preprint arXiv:2604.11748},
year={2026}
}