Added fine-tuned ESM2 Model

README.md

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+# ANTICP3: Anticancer Protein Prediction using ESM2
+
+This repository hosts the fine-tuned **ESM2-based classifier** for **anticancer protein (ACP) prediction**, named **ANTICP3**. The model is built on top of [facebook/esm2_t33_650M_UR50D](https://huggingface.co/facebook/esm2_t33_650M_UR50D), and it performs binary classification to predict whether a given protein or peptide sequence has anticancer properties.
+
+---
+
+## Model Details
+
+- **Base Model:** `facebook/esm2_t33_650M_UR50D`
+- **Task:** Binary Sequence Classification
+- **Labels:**  
+  - `0`: Non-Anticancer  
+  - `1`: Anticancer
+- **Framework:** [Transformers](https://huggingface.co/docs/transformers/index)  
+- **Format:** `Safetensors`
+
+---
+
+## 🚀 Usage
+
+You can load and use this model directly with the `transformers` library:
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
+model = AutoModelForSequenceClassification.from_pretrained("AmishaG/anticp3")
+
+# Example input sequence
+sequence = "MANCVVGYIGERCQYRDLKWWELRGGGGSGGGGSAPAFSVSPASGLSDGQSVSVSVSGAAAGETYYIAQCAPVGGQDACNPATATSFTTDASGAASFSFVVRKSYTGSTPEGTPVGSVDCATAACNLGAGNSGLDLGHVALTFGGGGGSGGGGSDHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCKLEHHHHHH"
+
+# Tokenize
+inputs = tokenizer(sequence, return_tensors="pt", truncation=True)
+
+# Run inference
+with torch.no_grad():
+    logits = model(**inputs).logits
+    probs = torch.nn.functional.softmax(logits, dim=-1)
+    prediction = torch.argmax(probs, dim=1).item()
+
+labels = {0: "Non-Anticancer", 1: "Anticancer"}
+print("Prediction:", labels[prediction])

config.json

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+{
+  "_name_or_path": "facebook/esm2_t33_650M_UR50D",
+  "architectures": [
+    "EsmForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout": null,
+  "emb_layer_norm_before": false,
+  "esmfold_config": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1280,
+  "initializer_range": 0.02,
+  "intermediate_size": 5120,
+  "is_folding_model": false,
+  "layer_norm_eps": 1e-05,
+  "mask_token_id": 32,
+  "max_position_embeddings": 1026,
+  "model_type": "esm",
+  "num_attention_heads": 20,
+  "num_hidden_layers": 33,
+  "pad_token_id": 1,
+  "position_embedding_type": "rotary",
+  "problem_type": "single_label_classification",
+  "token_dropout": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0",
+  "use_cache": true,
+  "vocab_list": null,
+  "vocab_size": 33
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:79369d989baf8df87877c7c397141e889cd796096e0df074ca23a5e56edceab4
+size 2609497900