Create README.md

README.md

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+## How to Use
+### Build any downstream models from this backbone
+#### Embedding
+```python
+from genbio_finetune.tasks import Embed
+model = Embed.from_config({"model.backbone": "proteinfm_v1"}).eval()
+collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
+embedding = model(collated_batch)
+print(embedding.shape)
+print(embedding)
+```
+#### Sequence Level Classification
+```python
+import torch
+from genbio_finetune.tasks import SequenceClassification
+model = SequenceClassification.from_config({"model.backbone": "proteinfm_v1", "model.n_classes": 2}).eval()
+collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
+logits = model(collated_batch)
+print(logits)
+print(torch.argmax(logits, dim=-1))
+```
+#### Token Level Classification
+```python
+import torch
+from genbio_finetune.tasks import TokenClassification
+model = TokenClassification.from_config({"model.backbone": "proteinfm_v1", "model.n_classes": 3}).eval()
+collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
+logits = model(collated_batch)
+print(logits)
+print(torch.argmax(logits, dim=-1))
+```
+#### Regression
+```python
+from genbio_finetune.tasks import SequenceRegression
+model = SequenceRegression.from_config({"model.backbone": "proteinfm_v1"}).eval()
+collated_batch = model.collate({"sequences": ["ACGT", "AGCT"]})
+logits = model(collated_batch)
+print(logits)
+```
+#### Protein-Protein Interaction
+
+#### Or use our one-liner CLI to finetune or evaluate any of the above!
+```
+gbft fit --model SequenceClassification --model.backbone proteinfm_v1 --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
+gbft test --model SequenceClassification --model.backbone proteinfm_v1 --data SequenceClassification --data.path <hf_or_local_path_to_your_dataset>
+```
+For more information, visit: [Model Generator](https://github.com/genbio-ai/modelgenerator)