DeepFold3

Weights for DeepFold3, a PyTorch biomolecular complex structure predictor architecturally equivalent to AlphaFold 3. Each .safetensors file embeds its architectural ModelConfig as JSON in the header (model_cfg_json), so deepfold3 inference rebuilds the trained architecture without a sidecar config.

Checkpoints

File	Run	Step	Snapshot	Params	SHA-256
df3-stage1-r19/checkpoint_120000.safetensors	df3-stage1-r19	120,000	EMA shadow (decay 0.999)	310,190,170 (fp32)	aef0468336c0a0ed7ecdadbb5397cfbfe3de0c552b72957dc77b6d1fea29ba2e

df3-stage1-r19 @ 120k

Architecture (r19). The trunk has no triangle attention and no single track: each PairFormer block is TriMulOutgoing + TriMulIncoming (plain AF3 TriangleMul) + FFN. Diffusion conditioning does not consume the trunk single (conditioning_use_trunk_single: false). The confidence-head and template PairFormers are unchanged from AF3.

pair / single / MSA channels	256 / 384 / 128
PairFormer layers	48
MSA module layers	4
Diffusion transformer blocks	24
Confidence PairFormer layers	4
Recycles	10

Training.

• Stage 0 from scratch (configs/df3-stage0-r19.yaml) to step 71,000, then stage 1 (configs/stage1.yaml: 512-token crop, bond loss on, shape-complementarity loss 0.03) resumed from that checkpoint.
• AdamW, lr 9e-4, EMA decay 0.999, 112 GPUs.
• Dataset mix (weights at step 120k): OpenFold3 pdb_training_set 0.5, OF3 long monomers 0.2, AFDB (NVIDIA) 0.15, TEDdymer 0.1, OF3 short monomers 0.05. The weighted PDB set was patchr until step 20,000.
• Step 120,000 is the optimizer step (effective_step). The checkpoint's global_step is 169,000 because stage 1 accumulates 2 micro-batches per step.

Export. deepfold3 export --snapshot auto from runs/df3-stage1-r19/checkpoint_120000.pt (commit 131baf6). The run is AdamW + EMA, so auto selects the EMA shadow (the deployment snapshot used by inference and eval). Verified bitwise-identical to the checkpoint's shadow overlay; loads into DeepFold3 with no missing or unexpected keys.

Usage

hf download vv137/deepfold3 df3-stage1-r19/checkpoint_120000.safetensors --local-dir weights/
deepfold3 inference --json input.json --output out/ \
    --params weights/df3-stage1-r19/checkpoint_120000.safetensors