Update FastPLMs files

README.md

@@ -139,11 +139,11 @@ Pooling excludes boundary, padding, sentinel, and other non-biological
 positions. Persisted results record the selected stack, layer, inputs, masks,
 and alignment policy.
 
-## 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
@@ -286,10 +286,10 @@ masked-LM extension and is not an official ANKH head.
 ## Release record
 
 - FastPLMs weights: `Synthyra/ANKH_large`
-- 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: `e498a2e9aea76ef784cbe3e596c6b3f5e9a40e209ad837f7e3207099e4d74483`
-- 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: `ElnaggarLab/ankh-large`
 - Artifact source: `official`
 - State transform: `ankh_t5_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 != "5008fbb18bb3259b0c0dfeac2f6d4d4bb4ccd97ba641905964ccd97de180f3fb":
+if RUNTIME_HASH != "79ee3a7bf063ea585f9792fb4d9292002767ca533625797d26c9f7ce5e14ca9e":
     raise RuntimeError("FastPLMs runtime identity differs from the bridge.")
 
 _RUNTIME_TEMPORARIES = []
@@ -179,16 +180,16 @@ def _install_runtime():
     return package
 
 _install_runtime()
-_module_181 = _import_without_bytecode("fastplms.models.ankh.modeling_ankh")
-FastAnkhConfig = _module_181.FastAnkhConfig
+_module_182 = _import_without_bytecode("fastplms.models.ankh.modeling_ankh")
+FastAnkhConfig = _module_182.FastAnkhConfig
 FastAnkhConfig.__module__ = __name__
-FastAnkhForConditionalGeneration = _module_181.FastAnkhForConditionalGeneration
+FastAnkhForConditionalGeneration = _module_182.FastAnkhForConditionalGeneration
 FastAnkhForConditionalGeneration.__module__ = __name__
-FastAnkhForMaskedLMExtension = _module_181.FastAnkhForMaskedLMExtension
+FastAnkhForMaskedLMExtension = _module_182.FastAnkhForMaskedLMExtension
 FastAnkhForMaskedLMExtension.__module__ = __name__
-FastAnkhForSequenceClassification = _module_181.FastAnkhForSequenceClassification
+FastAnkhForSequenceClassification = _module_182.FastAnkhForSequenceClassification
 FastAnkhForSequenceClassification.__module__ = __name__
-FastAnkhForTokenClassification = _module_181.FastAnkhForTokenClassification
+FastAnkhForTokenClassification = _module_182.FastAnkhForTokenClassification
 FastAnkhForTokenClassification.__module__ = __name__
-FastAnkhModel = _module_181.FastAnkhModel
+FastAnkhModel = _module_182.FastAnkhModel
 FastAnkhModel.__module__ = __name__