Feature Extraction
Transformers
Safetensors
esmfold2
biology
protein-structure
multimodal-protein-model
custom_code
Instructions to use Synthyra/ESMFold2-Fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMFold2-Fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/ESMFold2-Fast", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/ESMFold2-Fast", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- README.md +4 -4
- esmfold2_metrics.py +1 -1
- esmfold2_mmcif_parsing.py +1 -1
- esmfold2_molecular_complex.py +1 -1
- esmfold2_protein_chain.py +1 -1
- esmfold2_protein_complex.py +1 -1
- esmfold2_protein_structure.py +1 -1
README.md
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---
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library_name: transformers
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tags:
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- biology
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- protein-structure
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- esmfold2
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-
- multimodal-protein-model
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---
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# FastPLMs ESMFold2
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---
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library_name: transformers
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tags:
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- biology
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- protein-structure
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- esmfold2
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- multimodal-protein-model
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---
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# FastPLMs ESMFold2
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esmfold2_metrics.py
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@@ -5,7 +5,7 @@ from einops import rearrange
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from torch import Tensor
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from torch.amp import autocast # type: ignore
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from . import esmfold2_residue_constants
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from .esmfold2_misc import binpack, unbinpack
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from .esmfold2_protein_structure import (
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compute_alignment_tensors,
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from torch import Tensor
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from torch.amp import autocast # type: ignore
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from . import esmfold2_residue_constants as residue_constants
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from .esmfold2_misc import binpack, unbinpack
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from .esmfold2_protein_structure import (
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compute_alignment_tensors,
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esmfold2_mmcif_parsing.py
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import biotite.structure as bs
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import biotite.structure.io.pdbx as pdbx
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from . import esmfold2_residue_constants
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# Define PathOrBuffer for the opensource version
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PathOrBuffer = Union[str, os.PathLike, io.StringIO]
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import biotite.structure as bs
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import biotite.structure.io.pdbx as pdbx
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from . import esmfold2_residue_constants as residue_constants
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# Define PathOrBuffer for the opensource version
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PathOrBuffer = Union[str, os.PathLike, io.StringIO]
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esmfold2_molecular_complex.py
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set_structure,
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)
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from . import esmfold2_residue_constants
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from .esmfold2_metrics import compute_lddt, compute_rmsd
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from .esmfold2_protein_complex import ProteinComplex, ProteinComplexMetadata
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set_structure,
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)
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from . import esmfold2_residue_constants as residue_constants
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from .esmfold2_metrics import compute_lddt, compute_rmsd
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from .esmfold2_protein_complex import ProteinComplex, ProteinComplexMetadata
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esmfold2_protein_chain.py
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@@ -20,7 +20,7 @@ from biotite.structure.io.pdbx import set_structure as set_structure_pdbx
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from scipy.spatial import ConvexHull, KDTree
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from scipy.spatial.distance import cdist, pdist, squareform
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from . import esmfold2_residue_constants
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from .esmfold2_misc import slice_python_object_as_numpy
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from .esmfold2_affine3d import Affine3D
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from .esmfold2_aligner import Aligner
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from scipy.spatial import ConvexHull, KDTree
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from scipy.spatial.distance import cdist, pdist, squareform
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from . import esmfold2_residue_constants as residue_constants
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from .esmfold2_misc import slice_python_object_as_numpy
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from .esmfold2_affine3d import Affine3D
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from .esmfold2_aligner import Aligner
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esmfold2_protein_complex.py
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from biotite.structure.util import matrix_rotate
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from scipy.spatial import KDTree
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-
from . import esmfold2_residue_constants
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from .esmfold2_misc import slice_python_object_as_numpy
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from .esmfold2_affine3d import Affine3D
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from .esmfold2_aligner import Aligner
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from biotite.structure.util import matrix_rotate
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from scipy.spatial import KDTree
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from . import esmfold2_residue_constants as residue_constants
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from .esmfold2_misc import slice_python_object_as_numpy
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from .esmfold2_affine3d import Affine3D
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from .esmfold2_aligner import Aligner
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esmfold2_protein_structure.py
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@@ -8,7 +8,7 @@ import torch.nn.functional as F
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from torch import Tensor
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from torch.amp import autocast # type: ignore
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from . import esmfold2_residue_constants
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from .esmfold2_misc import unbinpack
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from .esmfold2_affine3d import Affine3D
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from torch import Tensor
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from torch.amp import autocast # type: ignore
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from . import esmfold2_residue_constants as residue_constants
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from .esmfold2_misc import unbinpack
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from .esmfold2_affine3d import Affine3D
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