Instructions to use YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
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Download README.md from YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b: direct link, hf CLI and curl.
- Browser
- Download file 1.9 kB
-
https://huggingface.co/YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b/resolve/main/README.md
- Command line
-
hf download hf://YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b/README.md
-
curl -L -o README.md https://huggingface.co/YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b/resolve/main/README.md
1.9 kB
metadata
license: mit
base_model: Dream-org/Dream-v0-Instruct-7B
tags:
- dllm-prm-gap
- discrete-diffusion
- gsm8k
- process-reward-model
- dream-7b
pipeline_tag: text-classification
library_name: peft
dLLM PRM Gap · Bidirectional PRM
News
- 2026-09: Accepted at NeurIPS 2026.
Public adapter release for dLLM PRM Gap. bidirectional attention with mask-aware mean pooling over intermediate denoising states
This repository contains only trainable adapter parameters and the reward head. It does not include the base model. The release configuration is recorded in
config.json; the arXiv paper defines the release scope and citation.
Files
adapter.safetensors— compact adapter weightsconfig.json— public base-model id, architecture, and provenance
Load
from huggingface_hub import snapshot_download
from prm.checkpointing import load_diffusion_prm
path = snapshot_download("YanZhanPKU/dLLM-PRM-Gap-bidir-dream7b")
model, report = load_diffusion_prm(
checkpoint=path,
model_path="Dream-org/Dream-v0-Instruct-7B",
local_files_only=False,
)
Role: process-reward model used by PRM Guided, Hybrid, and the snapshot diagnostics.
Paper: https://arxiv.org/abs/2609.35472.