Spaces:
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Update app.py
Browse filesremoving precision for now
app.py
CHANGED
@@ -35,22 +35,6 @@ class WeightType(Enum):
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Original = ModelDetails("Original")
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Delta = ModelDetails("Delta")
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class Precision(Enum):
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float16 = ModelDetails("float16")
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bfloat16 = ModelDetails("bfloat16")
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float32 = ModelDetails("float32")
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bfloat32 = ModelDetails("bfloat32")
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Unknown = ModelDetails("?")
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def from_str(precision):
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if precision in ["torch.float16", "float16"]:
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return Precision.float16
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if precision in ["torch.bfloat16", "bfloat16"]:
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return Precision.bfloat16
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if precision in ["torch.bfloat32", "bfloat32"]:
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return Precision.bfloat32
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if precision in ["torch.float32", "float32"]:
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return Precision.float32
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class ModelType(Enum):
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PT = ModelDetails(name="pretrained", symbol="🟢")
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@@ -83,26 +67,21 @@ def start_compute_space():
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return f"Okay! {COMPUTE_SPACE} should be running now!"
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def get_model_size(model_info: ModelInfo
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"""Gets the model size from the configuration, or the model name if the configuration does not contain the information."""
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try:
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model_size = round(model_info.safetensors["total"] / 1e9, 3)
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except (AttributeError, TypeError):
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return 0 # Unknown model sizes are indicated as 0, see NUMERIC_INTERVALS in app.py
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size_factor = 8 if (precision == "GPTQ" or "gptq" in model_info.modelId.lower()) else 1
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model_size = size_factor * model_size
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return model_size
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def add_new_eval(
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repo_id: str,
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precision: str,
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task: str,
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):
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model_owner = repo_id.split("/")[0]
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model_name = repo_id.split("/")[1]
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precision = precision.split(" ")[0]
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current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
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@@ -114,7 +93,7 @@ def add_new_eval(
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return
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# return styled_error("Could not get your model information. Please fill it up properly.")
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model_size = get_model_size(model_info=model_info
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print("Adding request")
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@@ -122,7 +101,7 @@ def add_new_eval(
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request_dict = {
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"model": repo_id,
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"precision":
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"status": "PENDING",
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"submitted_time": pd.to_datetime(current_time),
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"task": task,
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@@ -158,18 +137,12 @@ with gr.Blocks() as demo:
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task = gr.Dropdown(
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choices=tasks,
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label="Choose a benchmark task",
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multiselect=False,
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interactive=True,
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)
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with gr.Column():
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model_name_textbox = gr.Textbox(label="Model name")
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precision = gr.Dropdown(
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choices=[i.value.name for i in Precision if i != Precision.Unknown],
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label="Precision",
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multiselect=False,
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value="float16",
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interactive=True,
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)
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with gr.Row():
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with gr.Column():
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@@ -179,7 +152,6 @@ with gr.Blocks() as demo:
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fn=add_new_eval,
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inputs=[
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model_name_textbox,
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precision,
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task,
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],
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outputs=submission_result,
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Original = ModelDetails("Original")
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Delta = ModelDetails("Delta")
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class ModelType(Enum):
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PT = ModelDetails(name="pretrained", symbol="🟢")
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return f"Okay! {COMPUTE_SPACE} should be running now!"
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def get_model_size(model_info: ModelInfo):
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"""Gets the model size from the configuration, or the model name if the configuration does not contain the information."""
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try:
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model_size = round(model_info.safetensors["total"] / 1e9, 3)
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except (AttributeError, TypeError):
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return 0 # Unknown model sizes are indicated as 0, see NUMERIC_INTERVALS in app.py
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return model_size
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def add_new_eval(
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repo_id: str,
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task: str,
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):
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model_owner = repo_id.split("/")[0]
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model_name = repo_id.split("/")[1]
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current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
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return
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# return styled_error("Could not get your model information. Please fill it up properly.")
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model_size = get_model_size(model_info=model_info)
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print("Adding request")
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request_dict = {
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"model": repo_id,
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"precision": "N/A",
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"status": "PENDING",
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"submitted_time": pd.to_datetime(current_time),
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"task": task,
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task = gr.Dropdown(
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choices=tasks,
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label="Choose a benchmark task",
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value = 'Text Generation',
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multiselect=False,
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interactive=True,
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)
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with gr.Column():
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model_name_textbox = gr.Textbox(label="Model name")
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with gr.Row():
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with gr.Column():
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fn=add_new_eval,
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inputs=[
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model_name_textbox,
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task,
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],
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outputs=submission_result,
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