Instructions to use Synthyra/Profluent-E1-600M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/Profluent-E1-600M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/Profluent-E1-600M", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/Profluent-E1-600M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Third-party notices | |
| FastPLMs implements interfaces and checkpoint mappings for independently | |
| released protein models. The pinned repositories under `vendor/upstream/` are | |
| parity oracles. Production code does not import them, and runtime images do not | |
| contain them. | |
| This notice is informational and is not legal advice. A checkpoint license can | |
| differ from the license covering its source implementation. The typed inventory | |
| in `src/fastplms/models.toml` and the verbatim files under `LICENSES/` are the | |
| distribution record. | |
| ## ANKH | |
| The pinned ANKH implementation and the mirrored ANKH checkpoints are identified | |
| as CC BY-NC-SA 4.0. FastPLMs displays those terms but does not enforce them in | |
| software. Users are responsible for determining whether their use and | |
| redistribution comply. The complete text is in `LICENSES/ankh/LICENSE.md`. | |
| ## Profluent-E1 | |
| Profluent identifies its E1 model code as Apache-2.0. The E1 weights and full | |
| release are subject to the Profluent-E1 Clickthrough License Agreement and the | |
| incorporated attribution requirements. Any E1 distribution must retain all of | |
| the following files: | |
| - `LICENSES/e1/LICENSE`, the Profluent-E1 agreement | |
| - `LICENSES/e1/ATTRIBUTION`, the attribution guidelines | |
| - `LICENSES/e1/NOTICE`, the required notice | |
| - `LICENSES/e1/Apache-2.0.txt`, the code license | |
| - `LICENSES/e1/BSD-3-Clause.txt`, covering the FlashAttention-derived padding | |
| utility identified by the official E1 source | |
| - `LICENSES/e1/MODIFICATIONS.md`, the FastPLMs modified-file notice | |
| The exact text `Profluent-E1` must remain prominently displayed in E1 | |
| documentation and at each launch of an executable E1 workflow, as required by | |
| the upstream attribution guidelines. Certain commercial outputs, including | |
| specified pharmaceutical and target-related outputs, can require the separate | |
| `Built with Profluent-E1` statement described in `ATTRIBUTION`. | |
| ## DPLM | |
| The pinned ByteDance DPLM repository is Apache-2.0. Its | |
| [README](https://github.com/bytedance/dplm/blob/8a2e15e53416b4536f03f79ad1f6f6a9cbd5e19d/README.md#overview) | |
| explicitly defines the repository release as including pretrained DPLM1 and | |
| DPLM2 weights, and the same revision carries the complete | |
| [Apache-2.0 license](https://github.com/bytedance/dplm/blob/8a2e15e53416b4536f03f79ad1f6f6a9cbd5e19d/LICENSE). | |
| FastPLMs records both checkpoint families as Apache-2.0 and distributes the | |
| verbatim license plus `LICENSES/dplm/PROVENANCE.md`. Converted weights retain | |
| those terms and remain subject to the ordinary artifact and publication gates. | |
| ## Biohub | |
| The pinned Biohub ESM implementation is MIT and includes a separate | |
| `THIRD_PARTY_NOTICE.md`; both files are distributed under | |
| `LICENSES/biohub-esm/`. The pinned Biohub Transformers fork is Apache-2.0, with | |
| its complete text under `LICENSES/biohub-transformers/`. | |
| ## Boltz | |
| The pinned Boltz source is MIT. The verbatim notice is in | |
| `LICENSES/boltz/LICENSE`. | |
| ## Meta ESM and OpenFold | |
| The pinned Meta ESM source is MIT. The pinned OpenFold source is Apache-2.0. | |
| Their verbatim texts and revision-specific provenance notices are under | |
| `LICENSES/fair-esm/` and `LICENSES/openfold/`. | |
| The native H100 ESMFold reference image applies the tracked | |
| `docker/constraints/openfold-sm90.patch` to the copied OpenFold `setup.py`. | |
| This build-only change restricts the CUDA extension to `sm90` and selects the | |
| C++17 standard required by the reference PyTorch version. It leaves the pinned | |
| submodule, extension source, model classes, checkpoint data, and public API | |
| unchanged. The complete modified-file record is in | |
| `LICENSES/openfold/MODIFICATIONS.md`. | |
| The isolated reference image also includes Apache-2.0 PyTorch Lightning, | |
| TorchMetrics, Lightning Utilities, and NVIDIA DLLogger. Their exact versions or | |
| revision are pinned in `docker/constraints/esmfold.txt`; OpenFold imports them | |
| eagerly, and FastPLMs production code does not depend on them. DLLogger's exact | |
| source identity and installed-license handling are recorded in | |
| `LICENSES/dllogger/PROVENANCE.md`. | |
| ## ProteinTTT | |
| The optional test-time training workflow is validated against the pinned | |
| ProteinTTT repository under its MIT license. Its verbatim license and | |
| revision-specific provenance are under `LICENSES/protein-ttt/`. | |
| ## Conversion and packaging record | |
| For every supported family, `src/fastplms/models.toml` records an immutable | |
| official checkpoint revision, an immutable FastPLMs checkpoint revision, file | |
| digests, a named state transformation, and a mechanism-level conversion record. | |
| Generated artifacts reproduce that record in `provenance.json`. A release or | |
| artifact build must fail when a required file identity, legal text, attribution | |
| notice, modified-file notice, upstream revision, or conversion record is absent | |
| or differs from its manifest digest. | |