Instructions to use Synthyra/DPLM-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/DPLM-650M with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import EsmForDPLM model = EsmForDPLM.from_pretrained("Synthyra/DPLM-650M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update FastPLMs runtime files
Browse filesAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.
- README.md +4 -5
- config.json +3 -3
- runtime-attestation.json +5 -5
README.md
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## Install and platform requirements
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Install
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```bash
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python -m pip install \
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"fastplms @ git+https://github.com/Synthyra/FastPLMs.git
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```
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Python 3.11-3.14, PyTorch 2.13, and Transformers 5.13 are required. Eager, SDPA, and Flex use the core install. FlashAttention requires the `flash` extra, compatible CUDA hardware, and BF16 execution. The Hub quick start below requires network
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## Release record
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- FastPLMs weights: `Synthyra/DPLM-650M`
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- Runtime revision:
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- Runtime bundle SHA-256: `4999816c6b9cf8c297d6ed91df4087eb79a75e7d589d7f3fd47d542be89e59ea`
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- Generator/schema version and complete/runtime-only attestations: recorded in `provenance.json`
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- Official checkpoint: `airkingbd/dplm_650m`
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- Artifact source: `fast`
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## Install and platform requirements
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Install the current FastPLMs package:
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```bash
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python -m pip install \
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"fastplms @ git+https://github.com/Synthyra/FastPLMs.git"
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```
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Python 3.11-3.14, PyTorch 2.13, and Transformers 5.13 are required. Eager, SDPA, and Flex use the core install. FlashAttention requires the `flash` extra, compatible CUDA hardware, and BF16 execution. The Hub quick start below requires network
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## Release record
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- FastPLMs weights: `Synthyra/DPLM-650M`
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- Runtime revision: recorded separately in the built artifact and published commit
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- Source-tree and runtime-bundle SHA-256: recorded in `provenance.json`
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- Generator/schema version and complete/runtime-only attestations: recorded in `provenance.json`
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- Official checkpoint: `airkingbd/dplm_650m`
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- Artifact source: `fast`
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config.json
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"fastplms_checkpoint_repo_id": "Synthyra/DPLM-650M",
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"fastplms_checkpoint_revision": "05dc16d97c5c028aed924c9ed681cee4ab609760",
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"fastplms_model_id": "dplm_650m",
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"fastplms_release_tool_revision": "
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"fastplms_release_tool_sha256": "
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"fastplms_runtime_bundle_sha256": "4999816c6b9cf8c297d6ed91df4087eb79a75e7d589d7f3fd47d542be89e59ea",
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"fastplms_runtime_revision": "
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"fastplms_source_tree_sha256": "a62ff18405fc87b64b2d11a2d71f157ee3557e030055fccd6ca44aa376a95b41",
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"fastplms_weights_revision": "05dc16d97c5c028aed924c9ed681cee4ab609760",
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"hidden_act": "gelu",
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"fastplms_checkpoint_repo_id": "Synthyra/DPLM-650M",
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"fastplms_checkpoint_revision": "05dc16d97c5c028aed924c9ed681cee4ab609760",
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"fastplms_model_id": "dplm_650m",
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"fastplms_release_tool_revision": "95691a87c781f052f65b6ab3ca99dfce4ebb59c7",
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"fastplms_release_tool_sha256": "19b4247aba04a74de5069397518374ab2c3b9e0ce18ba9f36de34f0f4c5d1ceb",
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"fastplms_runtime_bundle_sha256": "4999816c6b9cf8c297d6ed91df4087eb79a75e7d589d7f3fd47d542be89e59ea",
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"fastplms_runtime_revision": "95691a87c781f052f65b6ab3ca99dfce4ebb59c7",
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"fastplms_source_tree_sha256": "a62ff18405fc87b64b2d11a2d71f157ee3557e030055fccd6ca44aa376a95b41",
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"fastplms_weights_revision": "05dc16d97c5c028aed924c9ed681cee4ab609760",
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"hidden_act": "gelu",
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runtime-attestation.json
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"LICENSES/FastPLMs-Apache-2.0.txt": "sha256:2d2b50c7b1414bff1189a1db1f0cfb92e3e064b50f4c2b1019827b683e1b629a",
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"LICENSES/dplm/LICENSE": "sha256:cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30",
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"LICENSES/dplm/PROVENANCE.md": "sha256:a659f74be9073cf1ad2d2f7071531ca56959b421f111152cf4c41184ace5970e",
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"README.md": "sha256:
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"THIRD_PARTY_NOTICES.md": "sha256:25704b3c76404696cae52e7fca13088d329f70f412687340351259e86cd62baa",
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"config.json": "sha256:
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"fastplms/__init__.py": "sha256:4fb3196022ca8ec699d59d09bdbc5f0184195552b773698ab9b061fe3cd7df12",
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"fastplms/attention/__init__.py": "sha256:f60b9fecfb4bcb37a4e7c26dc2f752b9035f9cbad627b4a84213f3a92ec88f7d",
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"fastplms/attention/_core.py": "sha256:8f7ec5b65bd8b6c6fa4951d50d1c0e499abf03ae00914794b51fc410201e3e33",
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},
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"model_id": "dplm_650m",
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"redistributable": true,
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"release_tool_revision": "
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"release_tool_sha256": "
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"runtime_bundle_sha256": "4999816c6b9cf8c297d6ed91df4087eb79a75e7d589d7f3fd47d542be89e59ea",
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"runtime_revision": "
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"schema_version": 2,
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"scope": "runtime-only",
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"source_tree_sha256": "a62ff18405fc87b64b2d11a2d71f157ee3557e030055fccd6ca44aa376a95b41",
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"LICENSES/FastPLMs-Apache-2.0.txt": "sha256:2d2b50c7b1414bff1189a1db1f0cfb92e3e064b50f4c2b1019827b683e1b629a",
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"LICENSES/dplm/LICENSE": "sha256:cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30",
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"LICENSES/dplm/PROVENANCE.md": "sha256:a659f74be9073cf1ad2d2f7071531ca56959b421f111152cf4c41184ace5970e",
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"README.md": "sha256:16a5e516f38d256aa7ad6a2dfed79a0610366a610c1e6aaf998cbd66c6325f19",
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"THIRD_PARTY_NOTICES.md": "sha256:25704b3c76404696cae52e7fca13088d329f70f412687340351259e86cd62baa",
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"config.json": "sha256:3c5414f46d5157f09367ef2a7f52f24a135379f3a90207b9020e33c5a5fe3eda",
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"fastplms/__init__.py": "sha256:4fb3196022ca8ec699d59d09bdbc5f0184195552b773698ab9b061fe3cd7df12",
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"fastplms/attention/__init__.py": "sha256:f60b9fecfb4bcb37a4e7c26dc2f752b9035f9cbad627b4a84213f3a92ec88f7d",
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"fastplms/attention/_core.py": "sha256:8f7ec5b65bd8b6c6fa4951d50d1c0e499abf03ae00914794b51fc410201e3e33",
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},
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"model_id": "dplm_650m",
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"redistributable": true,
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"release_tool_revision": "95691a87c781f052f65b6ab3ca99dfce4ebb59c7",
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"release_tool_sha256": "19b4247aba04a74de5069397518374ab2c3b9e0ce18ba9f36de34f0f4c5d1ceb",
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"runtime_bundle_sha256": "4999816c6b9cf8c297d6ed91df4087eb79a75e7d589d7f3fd47d542be89e59ea",
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"runtime_revision": "95691a87c781f052f65b6ab3ca99dfce4ebb59c7",
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"schema_version": 2,
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"scope": "runtime-only",
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"source_tree_sha256": "a62ff18405fc87b64b2d11a2d71f157ee3557e030055fccd6ca44aa376a95b41",
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