app.py
CHANGED
@@ -117,6 +117,10 @@ def generate_text_local(model_path, text):
|
|
117 |
logger.info(f"Running local text generation with {model_path}")
|
118 |
pipeline = pipelines[model_path]
|
119 |
|
|
|
|
|
|
|
|
|
120 |
# γγγ€γΉζ
ε ±γγγ°γ«θ¨ι²
|
121 |
device_info = next(pipeline.model.parameters()).device
|
122 |
logger.info(f"Model {model_path} is running on device: {device_info}")
|
@@ -127,6 +131,11 @@ def generate_text_local(model_path, text):
|
|
127 |
do_sample=False,
|
128 |
num_return_sequences=1
|
129 |
)
|
|
|
|
|
|
|
|
|
|
|
130 |
return outputs[0]["generated_text"]
|
131 |
except Exception as e:
|
132 |
logger.error(f"Error in local text generation with {model_path}: {str(e)}")
|
@@ -153,11 +162,20 @@ def classify_text_local(model_path, text):
|
|
153 |
logger.info(f"Running local classification with {model_path}")
|
154 |
pipeline = pipelines[model_path]
|
155 |
|
|
|
|
|
|
|
|
|
156 |
# γγγ€γΉζ
ε ±γγγ°γ«θ¨ι²
|
157 |
device_info = next(pipeline.model.parameters()).device
|
158 |
logger.info(f"Model {model_path} is running on device: {device_info}")
|
159 |
|
160 |
result = pipeline(text)
|
|
|
|
|
|
|
|
|
|
|
161 |
return str(result)
|
162 |
except Exception as e:
|
163 |
logger.error(f"Error in local classification with {model_path}: {str(e)}")
|
|
|
117 |
logger.info(f"Running local text generation with {model_path}")
|
118 |
pipeline = pipelines[model_path]
|
119 |
|
120 |
+
# γ’γγ«γζη€Ίηγ« GPU γ«η§»ε
|
121 |
+
if hasattr(pipeline.model, "to"):
|
122 |
+
pipeline.model.to("cuda")
|
123 |
+
|
124 |
# γγγ€γΉζ
ε ±γγγ°γ«θ¨ι²
|
125 |
device_info = next(pipeline.model.parameters()).device
|
126 |
logger.info(f"Model {model_path} is running on device: {device_info}")
|
|
|
131 |
do_sample=False,
|
132 |
num_return_sequences=1
|
133 |
)
|
134 |
+
|
135 |
+
# γ’γγ«γ CPU γ«ζ»γ
|
136 |
+
if hasattr(pipeline.model, "to"):
|
137 |
+
pipeline.model.to("cpu")
|
138 |
+
|
139 |
return outputs[0]["generated_text"]
|
140 |
except Exception as e:
|
141 |
logger.error(f"Error in local text generation with {model_path}: {str(e)}")
|
|
|
162 |
logger.info(f"Running local classification with {model_path}")
|
163 |
pipeline = pipelines[model_path]
|
164 |
|
165 |
+
# γ’γγ«γζη€Ίηγ« GPU γ«η§»ε
|
166 |
+
if hasattr(pipeline.model, "to"):
|
167 |
+
pipeline.model.to("cuda")
|
168 |
+
|
169 |
# γγγ€γΉζ
ε ±γγγ°γ«θ¨ι²
|
170 |
device_info = next(pipeline.model.parameters()).device
|
171 |
logger.info(f"Model {model_path} is running on device: {device_info}")
|
172 |
|
173 |
result = pipeline(text)
|
174 |
+
|
175 |
+
# γ’γγ«γ CPU γ«ζ»γ
|
176 |
+
if hasattr(pipeline.model, "to"):
|
177 |
+
pipeline.model.to("cpu")
|
178 |
+
|
179 |
return str(result)
|
180 |
except Exception as e:
|
181 |
logger.error(f"Error in local classification with {model_path}: {str(e)}")
|