Instructions to use isoformer-anonymous/Isoformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isoformer-anonymous/Isoformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="isoformer-anonymous/Isoformer", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("isoformer-anonymous/Isoformer", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update modeling_isoformer.py
Browse files- modeling_isoformer.py +4 -4
modeling_isoformer.py
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from isoformer_config import IsoformerConfig
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from transformers import PreTrainedModel
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from modeling_esm import NTForMaskedLM, MultiHeadAttention
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from esm_config import NTConfig
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from modeling_esm_original import EsmForMaskedLM
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from transformers.models.esm.configuration_esm import EsmConfig
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from enformer_pytorch import Enformer, str_to_one_hot, EnformerConfig
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import torch
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from .isoformer_config import IsoformerConfig
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from transformers import PreTrainedModel
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from .modeling_esm import NTForMaskedLM, MultiHeadAttention
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from .esm_config import NTConfig
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from .modeling_esm_original import EsmForMaskedLM
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from transformers.models.esm.configuration_esm import EsmConfig
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from enformer_pytorch import Enformer, str_to_one_hot, EnformerConfig
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import torch
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