remove newly ignored files

benchmark/stfr.py

@@ -1,57 +0,0 @@
-import os
-from pathlib import Path
-
-os.environ['LANG_MAIN_STOP_SEARCH_FOLDERNAME'] = 'tom-plugin'
-os.environ['LANG_MAIN_BASE_FOLDERNAME'] = 'tom-plugin'
-
-from lang_main.constants import SimilarityFunction
-from lang_main.model_loader import load_sentence_transformer as load_stfr
-from lang_main.types import (
-    ONNXExecutionProvider,
-    STFRBackends,
-    STFRDeviceTypes,
-    STFRModelArgs,
-    TorchDTypes,
-)
-
-MODEL_NAME = 'mixedbread-ai/deepset-mxbai-embed-de-large-v1'
-
-MODEL_ARGS: STFRModelArgs = {
-    # 'torch_dtype': 'float32',
-    'export': False,
-    # 'file_name': 'onnx/model_uint8.onnx',  # type: ignore
-    'file_name': 'onnx/model_quantized.onnx',  # type: ignore
-    'provider': ONNXExecutionProvider.CPU,
-}
-
-MODEL_PATH = Path(r'A:\Arbeitsaufgaben\lang-models')
-
-
-def load_models(model_name: str, trust_remote: bool = False, use_onnx: bool = False):
-    assert MODEL_PATH.exists(), 'model path not existing'
-    if use_onnx:
-        model_kwargs = MODEL_ARGS
-        backend = STFRBackends.ONNX
-    else:
-        model_kwargs = {'torch_dtype': 'float32'}
-        backend = STFRBackends.TORCH
-
-    stfr_model = load_stfr(
-        model_name=model_name,  # type: ignore
-        similarity_func=SimilarityFunction.COSINE,
-        backend=backend,
-        local_files_only=False,
-        trust_remote_code=trust_remote,
-        model_save_folder=str(MODEL_PATH),
-        model_kwargs=model_kwargs,
-    )
-
-    return stfr_model
-
-
-def main():
-    load_models(MODEL_NAME)
-
-
-if __name__ == '__main__':
-    main()

benchmark/test.toml

@@ -1,2 +0,0 @@
-[test]
-t1 = nan

tom-plugin.code-workspace

@@ -1,8 +0,0 @@
-{
-	"folders": [
-		{
-			"path": "."
-		}
-	],
-	"settings": {}
-}