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Update README.md
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README.md
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@@ -20,8 +20,8 @@ mgen test --model SequenceClassification --model.backbone aido_rna_1b600m_cds --
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```python
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from modelgenerator.tasks import Embed
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model = Embed.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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-
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embedding = model(
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print(embedding.shape)
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print(embedding)
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```
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@@ -30,8 +30,8 @@ print(embedding)
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import torch
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from modelgenerator.tasks import SequenceClassification
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model = SequenceClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 2}).eval()
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logits = model(
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print(logits)
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print(torch.argmax(logits, dim=-1))
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```
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@@ -40,8 +40,8 @@ print(torch.argmax(logits, dim=-1))
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import torch
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from modelgenerator.tasks import TokenClassification
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model = TokenClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 3}).eval()
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logits = model(
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print(logits)
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print(torch.argmax(logits, dim=-1))
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```
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@@ -49,8 +49,8 @@ print(torch.argmax(logits, dim=-1))
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```python
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from modelgenerator.tasks import SequenceRegression
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model = SequenceRegression.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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logits = model(
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print(logits)
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```
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@@ -58,8 +58,8 @@ print(logits)
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```python
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from genbio_finetune.tasks import Embed
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model = Embed.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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embedding = model(
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print(embedding.shape)
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print(embedding)
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```
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```python
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from modelgenerator.tasks import Embed
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model = Embed.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
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embedding = model(transformed_batch)
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print(embedding.shape)
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print(embedding)
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```
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import torch
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from modelgenerator.tasks import SequenceClassification
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model = SequenceClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 2}).eval()
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transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
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logits = model(transformed_batch)
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print(logits)
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print(torch.argmax(logits, dim=-1))
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```
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import torch
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from modelgenerator.tasks import TokenClassification
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model = TokenClassification.from_config({"model.backbone": "aido_rna_1b600m_cds", "model.n_classes": 3}).eval()
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transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
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logits = model(transformed_batch)
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print(logits)
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print(torch.argmax(logits, dim=-1))
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```
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```python
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from modelgenerator.tasks import SequenceRegression
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model = SequenceRegression.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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transformed_batch = model.transform({"sequences": ["ACGT", "AGCT"]})
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logits = model(transformed_batch)
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print(logits)
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```
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```python
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from genbio_finetune.tasks import Embed
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model = Embed.from_config({"model.backbone": "aido_rna_1b600m_cds"}).eval()
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transformed_batch = model.transform({"sequences": ["ACGT", "ACGT"]})
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embedding = model(transformed_batch)
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print(embedding.shape)
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print(embedding)
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```
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