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Update app.py
Browse filesI want it to get the new dataset version
app.py
CHANGED
@@ -17,9 +17,7 @@ COMPUTE_SPACE = f"{OWNER}/launch-computation-example"
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TOKEN = os.environ.get("DEBUG")
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API = HfApi(token=TOKEN)
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requests_dset = requests.to_pandas()
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model_list= requests_dset[requests_dset['status'] == 'COMPLETED']
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tasks = ['ASR', 'Object Detection', 'Text Classification', 'Image Captioning', 'Question Answering', 'Text Generation', 'Image Classification',
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'Sentence Similarity', 'Image Generation', 'Summarization']
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@@ -52,6 +50,9 @@ def add_new_eval(
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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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if repo_id in model_list['model'].tolist():
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return 'This model has already been run!'
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else:
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@@ -59,7 +60,6 @@ def add_new_eval(
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try:
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model_info = API.model_info(repo_id=repo_id)
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except Exception:
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-
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return "Could not find information for model %s" % (model)
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model_size = get_model_size(model_info=model_info)
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@@ -91,7 +91,11 @@ def add_new_eval(
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return start_compute_space()
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def print_existing_models():
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with gr.Blocks() as demo:
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gr.Markdown("# Energy Star Submission Portal - v.0 (2024) π π» π")
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TOKEN = os.environ.get("DEBUG")
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API = HfApi(token=TOKEN)
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+
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tasks = ['ASR', 'Object Detection', 'Text Classification', 'Image Captioning', 'Question Answering', 'Text Generation', 'Image Classification',
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'Sentence Similarity', 'Image Generation', 'Summarization']
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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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requests= load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN)
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requests_dset = requests.to_pandas()
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model_list= requests_dset[requests_dset['status'] == 'COMPLETED']
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if repo_id in model_list['model'].tolist():
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return 'This model has already been run!'
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else:
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try:
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model_info = API.model_info(repo_id=repo_id)
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except Exception:
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return "Could not find information for model %s" % (model)
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model_size = get_model_size(model_info=model_info)
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return start_compute_space()
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def print_existing_models():
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requests= load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN)
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requests_dset = requests.to_pandas()
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model_list= requests_dset[requests_dset['status'] == 'COMPLETED']
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return model_list
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with gr.Blocks() as demo:
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gr.Markdown("# Energy Star Submission Portal - v.0 (2024) π π» π")
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