Update FastPLMs files

README.md

@@ -97,11 +97,11 @@ Set `output` and `format="safetensors"` or `"sqlite"` for transactional,
 bounded-memory storage. Resume checks input order, model state, tokenizer
 policy, backend, dtype, and pooling configuration before it appends data.
 
-## Downstream classification
+## Downstream prediction
 
-Both downstream AutoClasses use the checkpoint backbone and create a new,
-untrained `classifier`. Sequence labels have shape `(b,)`. Residue labels have
-shape `(b, l)` and use `-100` outside biological positions:
+The sequence and token prediction AutoClasses use the checkpoint backbone and
+create a new, untrained `classifier`. Sequence labels have shape `(b,)`.
+Residue labels have shape `(b, l)` and use `-100` outside biological positions.
 
 ```python
 import torch
@@ -256,10 +256,10 @@ atomic-publication checks.
 ## Release record
 
 - FastPLMs weights: `Synthyra/DPLM2-650M`
-- Runtime revision: recorded in the built artifact and published commit
-- Source-tree and runtime-bundle SHA-256: recorded in the source record
-- Canonical transformed state SHA-256: `cba76b6602d2258de9fffff953b608d93cb8ef4a9e89b0bbd27e160c81e78bb4`
-- Conversion equality attestation: recorded in the source record
+- Runtime revision: recorded separately in the built artifact and published commit
+- Runtime source identities: recorded in `source-record.json`
+- Canonical transformed state identity: recorded in `source-record.json`
+- Conversion equality attestation: recorded in `source-record.json`
 - Official checkpoint: `airkingbd/dplm2_650m`
 - Artifact source: `official`
 - State transform: `dplm2_to_fastplms_v1`

fastplms/models.toml

@@ -199,7 +199,7 @@ representative = "esmc_small"
 documentation = "docs/models.md#esm-and-esmc"
 test_tiers = ["check", "compliance", "feature", "artifact", "benchmark"]
 runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/esm_plusplus", "models/ttt.py"]
-auto_map = { AutoConfig = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusConfig", AutoModel = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusModel", AutoModelForMaskedLM = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusForMaskedLM" }
+auto_map = { AutoConfig = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusConfig", AutoModel = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusModel", AutoModelForMaskedLM = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusForMaskedLM", AutoModelForSequenceClassification = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esm_plusplus.modeling_esm_plusplus.ESMplusplusForTokenClassification" }
 
 [families.esm3]
 architecture = "ESM3"
@@ -223,7 +223,7 @@ representative = "esm3_small"
 documentation = "docs/models.md#esm3"
 test_tiers = ["check", "compliance", "feature", "artifact", "benchmark"]
 runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/esm3", "models/ttt.py"]
-auto_map = { AutoConfig = "fastplms.models.esm3.modeling_esm3.FastESM3Config", AutoModel = "fastplms.models.esm3.modeling_esm3.FastESM3Model" }
+auto_map = { AutoConfig = "fastplms.models.esm3.modeling_esm3.FastESM3Config", AutoModel = "fastplms.models.esm3.modeling_esm3.FastESM3Model", AutoModelForSequenceClassification = "fastplms.models.esm3.modeling_esm3.FastESM3ForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esm3.modeling_esm3.FastESM3ForTokenClassification" }
 
 [families.e1]
 architecture = "E1"
@@ -370,8 +370,8 @@ conversion_provenance = "Input: the pinned native Meta ESMFold checkpoint plus i
 representative = "esmfold"
 documentation = "docs/models.md#esmfold"
 test_tiers = ["check", "compliance", "structure", "feature", "artifact", "benchmark"]
-runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/_esm_rotary.py", "models/esmfold"]
-auto_map = { AutoConfig = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmFoldConfig", AutoModel = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmForProteinFolding" }
+runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/_esm_rotary.py", "models/classification_probe.py", "models/esmfold"]
+auto_map = { AutoConfig = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmFoldConfig", AutoModel = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmForProteinFolding", AutoModelForSequenceClassification = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esmfold.modeling_fast_esmfold.FastEsmForTokenClassification" }
 
 [families.esmfold2]
 architecture = "ESMFold2"
@@ -396,8 +396,8 @@ conversion_provenance = "Input: each pinned Biohub ESMFold2 checkpoint and its s
 representative = "esmfold2"
 documentation = "docs/esmfold2.md"
 test_tiers = ["check", "compliance", "structure", "feature", "artifact", "benchmark"]
-runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/esmfold2", "models/esm_plusplus", "models/ttt.py"]
-auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2.ESMFold2Model" }
+runtime_paths = ["__init__.py", "registry.py", "runtime.py", "models.toml", "models/__init__.py", "attention", "embeddings", "models/classification_probe.py", "models/_esm_rotary.py", "models/esmfold2", "models/esm_plusplus", "models/ttt.py"]
+auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2.ESMFold2Model", AutoModelForSequenceClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ForTokenClassification" }
 
 [[models]]
 id = "esm2_8m"
@@ -1215,7 +1215,7 @@ official_files = [
   "config.json=git-sha1:79ed0dc0f867b8f09bfa004d6f77397c2ab9b38d",
   "model.safetensors=sha256:01358c317428d38535e3db513cab177336fc0f7fab0d84002e64b7741d5181b3",
 ]
-auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2_experimental.ESMFold2ExperimentalModel" }
+auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2_experimental.ESMFold2ExperimentalModel", AutoModelForSequenceClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ExperimentalForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ExperimentalForTokenClassification" }
 
 [[models]]
 id = "esmfold2_experimental_fast_cutoff2025"
@@ -1236,4 +1236,4 @@ official_files = [
   "config.json=git-sha1:0333d68ddb12ed2f066741dcb801142f466c0a2c",
   "model.safetensors=sha256:4e903b740ad6ad704ec60881bfd593e0d6c874a630ffa0f0838276e0b665088f",
 ]
-auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2_experimental.ESMFold2ExperimentalModel" }
+auto_map = { AutoConfig = "fastplms.models.esmfold2.configuration_esmfold2.ESMFold2Config", AutoModel = "fastplms.models.esmfold2.modeling_esmfold2_experimental.ESMFold2ExperimentalModel", AutoModelForSequenceClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ExperimentalForSequenceClassification", AutoModelForTokenClassification = "fastplms.models.esmfold2.modeling_esmfold2_classification.ESMFold2ExperimentalForTokenClassification" }

modeling_fastplms.py

@@ -8,11 +8,12 @@ import sys
 import tempfile
 from io import BytesIO
 from pathlib import Path
+from typing import ClassVar
 from zipfile import ZIP_DEFLATED, ZipFile
 
 from .fastplms_bundle import RUNTIME_DATA, RUNTIME_HASH
 
-if RUNTIME_HASH != "4d969d80a604669b287601091efc8c52de6fc4fd2c9b9c7140a1261e5cf2d4bc":
+if RUNTIME_HASH != "fbd2bd155dd56f7aec6b9a945997b33560902cd7ab7713458c81360ff3209cc4":
     raise RuntimeError("FastPLMs runtime identity differs from the bridge.")
 
 _RUNTIME_TEMPORARIES = []
@@ -179,17 +180,17 @@ def _install_runtime():
     return package
 
 _install_runtime()
-_module_181 = _import_without_bytecode("fastplms.models.dplm2.modeling_dplm2")
-DPLM2Config = _module_181.DPLM2Config
+_module_182 = _import_without_bytecode("fastplms.models.dplm2.modeling_dplm2")
+DPLM2Config = _module_182.DPLM2Config
 DPLM2Config.__module__ = __name__
-DPLM2ForMaskedLM = _module_181.DPLM2ForMaskedLM
+DPLM2ForMaskedLM = _module_182.DPLM2ForMaskedLM
 DPLM2ForMaskedLM.__module__ = __name__
-DPLM2ForSequenceClassification = _module_181.DPLM2ForSequenceClassification
+DPLM2ForSequenceClassification = _module_182.DPLM2ForSequenceClassification
 DPLM2ForSequenceClassification.__module__ = __name__
-DPLM2ForTokenClassification = _module_181.DPLM2ForTokenClassification
+DPLM2ForTokenClassification = _module_182.DPLM2ForTokenClassification
 DPLM2ForTokenClassification.__module__ = __name__
-DPLM2Model = _module_181.DPLM2Model
+DPLM2Model = _module_182.DPLM2Model
 DPLM2Model.__module__ = __name__
-_module_192 = _import_without_bytecode("fastplms.models.dplm2.tokenization_dplm2")
-DPLM2Tokenizer = _module_192.DPLM2Tokenizer
+_module_193 = _import_without_bytecode("fastplms.models.dplm2.tokenization_dplm2")
+DPLM2Tokenizer = _module_193.DPLM2Tokenizer
 DPLM2Tokenizer.__module__ = __name__