bofenghuang / doctomodernbert-fr-large-diffusion-v0.1

huggingface.co
Total runs: 62
24-hour runs: -3
7-day runs: -2
30-day runs: 23
Model's Last Updated: July 06 2026
text-generation

Introduction of doctomodernbert-fr-large-diffusion-v0.1

Model Details of doctomodernbert-fr-large-diffusion-v0.1

DoctoModernBERT-fr-large-diffusion-v0.1

demo

A text diffusion model based on DoctoModernBERT-fr-large , finetuned on a medical instruction-following dataset.

Unlike an autoregressive LLM, which decodes strictly left to right one token at a time, this model works by iterative denoising. It starts from a fully masked canvas and, at each step, predicts all masked positions at once and keeps only the most confident ones. It still moves through the sequence one block at a time, so generation is parallel inside each block but left to right across blocks.

This is an exploratory checkpoint. It's small and lightly trained, so expect mistakes and weaker answers.

🚀 How to Use

Training and generation are done through the dLLM library.

Setup
git clone https://github.com/ZHZisZZ/dllm
cd dllm
pip install -e .
Sampling
import dllm

model_id = "bofenghuang/doctomodernbert-fr-large-diffusion-v0.1"  # or a local path

model = dllm.utils.get_model(model_name_or_path=model_id).eval()
tokenizer = dllm.utils.get_tokenizer(model_name_or_path=model_id)
sampler = dllm.core.samplers.MDLMSampler(model=model, tokenizer=tokenizer)

config = dllm.core.samplers.MDLMSamplerConfig(
    steps=128,             # total diffusion steps
    max_new_tokens=128,    # length of the generated answer span
    block_size=32,         # semi-autoregressive block size
    temperature=0.0,       # 0.0 = greedy / low-confidence remasking
    remasking="low_confidence",
)

messages = [
    [{"role": "user", "content": "Quels sont les symptômes typiques d'une infection urinaire ?"}],
]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=True)
outputs = sampler.sample(inputs, config, return_dict=True)
print(dllm.utils.sample_trim(tokenizer, outputs.sequences.tolist(), inputs)[0])
Interactive chat
python -u examples/bert/chat.py --model_name_or_path "bofenghuang/doctomodernbert-fr-large-diffusion-v0.1"

The chat template wraps turns as [SYS] … [/SYS] , [Question] … [/Question] , [Answer] … [/Answer] .

Runs of bofenghuang doctomodernbert-fr-large-diffusion-v0.1 on huggingface.co

62
Total runs
-3
24-hour runs
-1
3-day runs
-2
7-day runs
23
30-day runs

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