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.ipynb_checkpoints/README-checkpoint.md

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+---
+tags:
+  - protein
+  - biology
+  - kinase
+  - sequence-classification
+---
+
+# Kinase–Substrate Interaction Classifier
+
+Fine-tuned from TAPE ProteinBERT (`bert-base`) on kinase–substrate pairs.
+
+## Input
+Concatenated kinase + `<sep>` + substrate amino acid sequences.
+
+## Output
+Binary classification: 1 = interaction, 0 = no interaction
+
+## SETUP ENV
+
+```
+pip install tensorboard
+pip install einops
+pip install scikit-learn
+pip install plotnine
+pip install seaborn
+pip install tape-proteins pandas numpy pyyaml tqdm scikit-learn tensorboard
+pip install transformers
+pip install torch
+```
+
+## Inference
+
+```
+from tape import ProteinBertForSequenceClassification, TAPETokenizer
+model = ProteinBertForSequenceClassification.from_pretrained("steveyu323/kinbert_v2_long")
+```

README.md

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+---
+tags:
+  - protein
+  - biology
+  - kinase
+  - sequence-classification
+---
+
+# Kinase–Substrate Interaction Classifier
+
+Fine-tuned from TAPE ProteinBERT (`bert-base`) on kinase–substrate pairs.
+
+## Input
+Concatenated kinase + `<sep>` + substrate amino acid sequences.
+
+## Output
+Binary classification: 1 = interaction, 0 = no interaction
+
+## SETUP ENV
+
+```
+pip install tensorboard
+pip install einops
+pip install scikit-learn
+pip install plotnine
+pip install seaborn
+pip install tape-proteins pandas numpy pyyaml tqdm scikit-learn tensorboard
+pip install transformers
+pip install torch
+```
+
+## Inference
+
+```
+from tape import ProteinBertForSequenceClassification, TAPETokenizer
+model = ProteinBertForSequenceClassification.from_pretrained("steveyu323/kinbert_v2_long")
+```

config.json

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+{
+  "attention_probs_dropout_prob": 0.1,
+  "base_model": "transformer",
+  "finetuning_task": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "input_size": 768,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 8192,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_labels": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "output_size": 768,
+  "pruned_heads": {},
+  "torchscript": false,
+  "type_vocab_size": 1,
+  "vocab_size": 30
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d2f9b809b19eaa854881efd895ed93165792da983ac112c0e617143a57c55fcf
+size 369507479

tokenizer_config.json

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+{"vocab": "iupac", "threshold": 0.7734375}