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| from argparse import Namespace | |
| from nomic import atlas | |
| import numpy as np | |
| from transformers import AutoModel | |
| import text | |
| num_embeddings = 10000 | |
| def download_models(): | |
| # Import our models. The package will take care of downloading the models automatically | |
| model_args = Namespace(do_mlm=None, pooler_type="cls", temp=0.05, mlp_only_train=False, | |
| init_embeddings_model=None) | |
| model = AutoModel.from_pretrained("silk-road/luotuo-bert", trust_remote_code=True, model_args=model_args) | |
| return model | |
| pkl_path = './pkl/texts.pkl' | |
| maps_path = './pkl/maps.pkl' | |
| dict_path = "../characters/haruhi/text_image_dict.txt" | |
| image_path = "../characters/haruhi/images" | |
| model = download_models() | |
| text = text.Text("../characters/haruhi/texts", model=model, num_steps=50, pkl_path=pkl_path, dict_path=dict_path, | |
| image_path=image_path, maps_path=maps_path) | |
| # text.read_text(save_maps=True, save_embeddings=True) | |
| embeddings = np.array([i.numpy() for i in list(text.load(load_pkl=True).values())]) | |
| data = text.load(load_maps=True) | |
| project = atlas.map_embeddings(embeddings=embeddings, | |
| data=data, | |
| build_topic_model=True, | |
| topic_label_field="titles", | |
| id_field='id', | |
| name="Chat-Haruhi", | |
| colorable_fields=['titles'], | |
| description="Embedding Visualization", | |
| # reset_project_if_exists=True, | |
| ) | |