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usage docstring
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‎src/boltz_binder_design/losses/esm.py‎

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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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#
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#
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# Pseudo-likelihood for the ESM-2 masked language model
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#
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# Usage:
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# import esm2quinox
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# import esm
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# torch_model, _ = esm.pretrained.esm2_t33_650M_UR50D()
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# ESM2PLL = ESM2PseudoLikelihood(esm2quinox.from_torch(torch_model))
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import jax
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import numpy as np

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