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from dataclasses import dataclass |
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@dataclass |
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class ColumnContent: |
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name: str |
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type: str |
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displayed_by_default: bool |
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hidden: bool = False |
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def fields(raw_class): |
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return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"] |
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@dataclass(frozen=True) |
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class AutoEvalColumn: |
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model_type_symbol = ColumnContent("T", "str", True) |
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model = ColumnContent("Model", "markdown", True) |
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average = ColumnContent("Average ⬆️", "number", True) |
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arc = ColumnContent("ARC", "number", True) |
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hellaswag = ColumnContent("HellaSwag", "number", True) |
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mmlu = ColumnContent("MMLU", "number", True) |
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truthfulqa = ColumnContent("TruthfulQA", "number", True) |
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model_type = ColumnContent("Type", "str", False) |
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precision = ColumnContent("Precision", "str", False, True) |
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license = ColumnContent("Hub License", "str", False) |
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params = ColumnContent("#Params (B)", "number", False) |
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likes = ColumnContent("Hub ❤️", "number", False) |
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revision = ColumnContent("Model sha", "str", False, False) |
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dummy = ColumnContent("model_name_for_query", "str", True) |
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@dataclass(frozen=True) |
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class EloEvalColumn: |
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model = ColumnContent("Model", "markdown", True) |
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gpt4 = ColumnContent("GPT-4 (all)", "number", True) |
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human_all = ColumnContent("Human (all)", "number", True) |
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human_instruct = ColumnContent("Human (instruct)", "number", True) |
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human_code_instruct = ColumnContent("Human (code-instruct)", "number", True) |
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@dataclass(frozen=True) |
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class EvalQueueColumn: |
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model = ColumnContent("model", "markdown", True) |
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revision = ColumnContent("revision", "str", True) |
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private = ColumnContent("private", "bool", True) |
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precision = ColumnContent("precision", "bool", True) |
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weight_type = ColumnContent("weight_type", "str", "Original") |
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status = ColumnContent("status", "str", True) |
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LLAMAS = ["huggingface/llama-7b", "huggingface/llama-13b", "huggingface/llama-30b", "huggingface/llama-65b"] |
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KOALA_LINK = "https://huggingface.co/TheBloke/koala-13B-HF" |
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VICUNA_LINK = "https://huggingface.co/lmsys/vicuna-13b-delta-v1.1" |
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OASST_LINK = "https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5" |
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DOLLY_LINK = "https://huggingface.co/databricks/dolly-v2-12b" |
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MODEL_PAGE = "https://huggingface.co/models" |
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LLAMA_LINK = "https://ai.facebook.com/blog/large-language-model-llama-meta-ai/" |
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VICUNA_LINK = "https://huggingface.co/CarperAI/stable-vicuna-13b-delta" |
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ALPACA_LINK = "https://crfm.stanford.edu/2023/03/13/alpaca.html" |
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def model_hyperlink(link, model_name): |
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return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>' |
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def make_clickable_model(model_name): |
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link = f"https://huggingface.co/{model_name}" |
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if model_name in LLAMAS: |
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link = LLAMA_LINK |
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model_name = model_name.split("/")[1] |
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elif model_name == "HuggingFaceH4/stable-vicuna-13b-2904": |
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link = VICUNA_LINK |
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model_name = "stable-vicuna-13b" |
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elif model_name == "HuggingFaceH4/llama-7b-ift-alpaca": |
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link = ALPACA_LINK |
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model_name = "alpaca-13b" |
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if model_name == "dolly-12b": |
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link = DOLLY_LINK |
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elif model_name == "vicuna-13b": |
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link = VICUNA_LINK |
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elif model_name == "koala-13b": |
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link = KOALA_LINK |
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elif model_name == "oasst-12b": |
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link = OASST_LINK |
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return model_hyperlink(link, model_name) |
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def styled_error(error): |
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return f"<p style='color: red; font-size: 20px; text-align: center;'>{error}</p>" |
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def styled_warning(warn): |
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return f"<p style='color: orange; font-size: 20px; text-align: center;'>{warn}</p>" |
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def styled_message(message): |
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return f"<p style='color: green; font-size: 20px; text-align: center;'>{message}</p>" |
