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import torch
from transformers import AutoTokenizer, GPT2Model
import torch.nn as nn
class ChessMoveClassifier(nn.Module):
def __init__(self, model_name, num_labels=4096):
super().__init__()
self.base_model = GPT2Model.from_pretrained(model_name)
self.dropout = nn.Dropout(0.1)
self.classifier = nn.Linear(self.base_model.config.n_embd, num_labels)
def forward(self, input_ids, attention_mask=None, **kwargs):
outputs = self.base_model(input_ids=input_ids, attention_mask=attention_mask)
hidden_state = outputs.last_hidden_state[:, -1, :]
logits = self.classifier(self.dropout(hidden_state))
return {"logits": logits}
def model_fn(model_dir):
model = ChessMoveClassifier(model_name="austindavis/ChessGPT_d12")
model.load_state_dict(torch.load(f"{model_dir}/model.pt", map_location="cpu"))
model.eval()
return model
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