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| # Utilities related to searching and posting on the Hub | |
| import os | |
| import webbrowser | |
| import pandas as pd | |
| from huggingface_hub import HfApi | |
| from model_utils import calculate_memory, extract_from_url, get_model | |
| def check_for_discussion(model_name: str): | |
| "Checks if an automated discussion has been opened on the model by `model-sizer-bot`" | |
| api = HfApi(token=os.environ.get("HUGGINGFACE_API_LOGIN", None)) | |
| model_name = extract_from_url(model_name) | |
| discussions = list(api.get_repo_discussions(model_name)) | |
| return any( | |
| discussion.title == "[AUTOMATED] Model Memory Requirements" and discussion.author == "model-sizer-bot" | |
| for discussion in discussions | |
| ) | |
| def report_results(model_name, library, access_token): | |
| "Reports the results of a memory calculation to the model's discussion page, and opens a new tab to it afterwards" | |
| model = get_model(model_name, library, access_token) | |
| data = calculate_memory(model, ["float32", "float16/bfloat16", "int8", "int4"]) | |
| df = pd.DataFrame(data).to_markdown(index=False) | |
| post = f"""# Model Memory Requirements\n | |
| You will need about {data[1]} VRAM to load this model for inference, and {data[3]} VRAM to train it using Adam. | |
| These calculations were measured from the [Model Memory Utility Space](https://hf.co/spaces/hf-accelerate/model-memory-utility) on the Hub. | |
| The minimum recommended vRAM needed for this model assumes using [Accelerate or `device_map="auto"`](https://huggingface.co/docs/accelerate/usage_guides/big_modeling) and is denoted by the size of the "largest layer". | |
| When performing inference, expect to add up to an additional 20% to this, as found by [EleutherAI](https://blog.eleuther.ai/transformer-math/). More tests will be performed in the future to get a more accurate benchmark for each model. | |
| When training with `Adam`, you can expect roughly 4x the reported results to be used. (1x for the model, 1x for the gradients, and 2x for the optimizer). | |
| ## Results: | |
| {df} | |
| """ | |
| api = HfApi(token=os.environ.get("HUGGINGFACE_API_LOGIN", None)) | |
| discussion = api.create_discussion(model_name, "[AUTOMATED] Model Memory Requirements", description=post) | |
| webbrowser.open_new_tab(discussion.url) | |