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Sai Vinay G
commited on
Commit
•
0f32a96
1
Parent(s):
212e5f2
updates
Browse files- README.md +0 -0
- app.py +2 -0
- requirements.txt +0 -0
- src/assets/css_html_js.py +0 -0
- src/assets/hardcoded_evals.py +3 -1
- src/assets/scale-hf-logo.png +0 -0
- src/assets/text_content.py +12 -2
- src/auto_leaderboard/get_model_metadata.py +1 -1
- src/auto_leaderboard/load_results.py +29 -10
- src/auto_leaderboard/model_metadata_type.py +368 -53
- src/init.py +0 -0
- src/utils_display.py +5 -4
README.md
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File without changes
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app.py
CHANGED
@@ -2,6 +2,8 @@ import json
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import os
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from datetime import datetime, timezone
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import gradio as gr
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import numpy as np
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import os
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from datetime import datetime, timezone
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os.environ["H4_TOKEN"]="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"
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os.environ["IS_PUBLIC"]="True"
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import gradio as gr
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import numpy as np
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requirements.txt
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File without changes
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src/assets/css_html_js.py
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File without changes
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src/assets/hardcoded_evals.py
CHANGED
@@ -10,6 +10,7 @@ gpt4_values = {
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AutoEvalColumn.mmlu.name: 86.4,
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AutoEvalColumn.truthfulqa.name: 59.0,
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AutoEvalColumn.dummy.name: "GPT-4",
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}
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gpt35_values = {
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@@ -22,6 +23,7 @@ gpt35_values = {
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AutoEvalColumn.mmlu.name: 70.0,
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AutoEvalColumn.truthfulqa.name: 47.0,
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AutoEvalColumn.dummy.name: "GPT-3.5",
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}
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baseline = {
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@@ -34,5 +36,5 @@ baseline = {
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AutoEvalColumn.mmlu.name: 25.0,
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AutoEvalColumn.truthfulqa.name: 25.0,
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AutoEvalColumn.dummy.name: "baseline",
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}
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-
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AutoEvalColumn.mmlu.name: 86.4,
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AutoEvalColumn.truthfulqa.name: 59.0,
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AutoEvalColumn.dummy.name: "GPT-4",
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AutoEvalColumn.model_type.name: "",
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}
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gpt35_values = {
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AutoEvalColumn.mmlu.name: 70.0,
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AutoEvalColumn.truthfulqa.name: 47.0,
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AutoEvalColumn.dummy.name: "GPT-3.5",
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AutoEvalColumn.model_type.name: "",
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}
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baseline = {
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AutoEvalColumn.mmlu.name: 25.0,
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AutoEvalColumn.truthfulqa.name: 25.0,
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AutoEvalColumn.dummy.name: "baseline",
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AutoEvalColumn.model_type.name: "",
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}
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src/assets/scale-hf-logo.png
CHANGED
Git LFS Details
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Git LFS Details
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src/assets/text_content.py
CHANGED
@@ -62,6 +62,8 @@ INTRODUCTION_TEXT = f"""
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🤗 Anyone from the community can submit a model for automated evaluation on the 🤗 GPU cluster, as long as it is a 🤗 Transformers model with weights on the Hub. We also support evaluation of models with delta-weights for non-commercial licensed models, such as the original LLaMa release.
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Other cool benchmarks for LLMs are developped at HuggingFace, go check them out: 🙋🤖 [human and GPT4 evals](https://huggingface.co/spaces/HuggingFaceH4/human_eval_llm_leaderboard), 🖥️ [performance benchmarks](https://huggingface.co/spaces/optimum/llm-perf-leaderboard)
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"""
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LLM_BENCHMARKS_TEXT = f"""
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- <a href="https://arxiv.org/abs/2009.03300" target="_blank"> MMLU </a> (5-shot) - a test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.
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- <a href="https://arxiv.org/abs/2109.07958" target="_blank"> TruthfulQA </a> (0-shot) - a test to measure a model’s propensity to reproduce falsehoods commonly found online. Note: TruthfulQA in the Harness is actually a minima a 6-shots task, as it is prepended by 6 examples systematically, even when launched using 0 for the number of few-shot examples.
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We chose these benchmarks as they test a variety of reasoning and general knowledge across a wide variety of fields in 0-shot and few-shot settings.
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# Some good practices before submitting a model
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- 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
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- 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
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# In case of model failure
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If your model is displayed in the `FAILED` category, its execution stopped.
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Make sure you have followed the above steps first.
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@@ -140,13 +150,13 @@ These models will be automatically evaluated on the 🤗 cluster.
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"""
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CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
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CITATION_BUTTON_TEXT = r"""
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author = {Edward Beeching, Clémentine Fourrier, Nathan Habib, Sheon Han, Nathan Lambert, Nazneen Rajani, Omar Sanseviero, Lewis Tunstall, Thomas Wolf},
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title = {Open LLM Leaderboard},
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year = {2023},
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publisher = {Hugging Face},
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howpublished = "\url{https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard}"
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-
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}
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@software{eval-harness,
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author = {Gao, Leo and
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🤗 Anyone from the community can submit a model for automated evaluation on the 🤗 GPU cluster, as long as it is a 🤗 Transformers model with weights on the Hub. We also support evaluation of models with delta-weights for non-commercial licensed models, such as the original LLaMa release.
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Other cool benchmarks for LLMs are developped at HuggingFace, go check them out: 🙋🤖 [human and GPT4 evals](https://huggingface.co/spaces/HuggingFaceH4/human_eval_llm_leaderboard), 🖥️ [performance benchmarks](https://huggingface.co/spaces/optimum/llm-perf-leaderboard)
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🟢: Base pretrained model – 🔶: Instruction finetuned model – 🟦: Model finetuned with RL (read more details in "About" tab)
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"""
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LLM_BENCHMARKS_TEXT = f"""
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- <a href="https://arxiv.org/abs/2009.03300" target="_blank"> MMLU </a> (5-shot) - a test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.
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- <a href="https://arxiv.org/abs/2109.07958" target="_blank"> TruthfulQA </a> (0-shot) - a test to measure a model’s propensity to reproduce falsehoods commonly found online. Note: TruthfulQA in the Harness is actually a minima a 6-shots task, as it is prepended by 6 examples systematically, even when launched using 0 for the number of few-shot examples.
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For all these evaluations, a higher score is a better score.
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We chose these benchmarks as they test a variety of reasoning and general knowledge across a wide variety of fields in 0-shot and few-shot settings.
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# Some good practices before submitting a model
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- 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
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- 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
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### Icons
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🟢 means that the model is pretrained
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🔶 that it is finetuned
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🟦 that is was trained with RL.
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If there is no icon, we have not uploaded the information on the model yet, feel free to open an issue with the model information!
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# In case of model failure
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If your model is displayed in the `FAILED` category, its execution stopped.
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Make sure you have followed the above steps first.
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"""
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CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
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CITATION_BUTTON_TEXT = r"""
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@misc{open-llm-leaderboard,
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author = {Edward Beeching, Clémentine Fourrier, Nathan Habib, Sheon Han, Nathan Lambert, Nazneen Rajani, Omar Sanseviero, Lewis Tunstall, Thomas Wolf},
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title = {Open LLM Leaderboard},
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year = {2023},
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publisher = {Hugging Face},
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howpublished = "\url{https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard}"
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}
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@software{eval-harness,
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author = {Gao, Leo and
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src/auto_leaderboard/get_model_metadata.py
CHANGED
@@ -53,4 +53,4 @@ def get_model_size(model_name, model_info):
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def apply_metadata(leaderboard_data: List[dict]):
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get_model_type(leaderboard_data)
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get_model_infos_from_hub(leaderboard_data)
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def apply_metadata(leaderboard_data: List[dict]):
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get_model_type(leaderboard_data)
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get_model_infos_from_hub(leaderboard_data)
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src/auto_leaderboard/load_results.py
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@@ -4,6 +4,7 @@ import glob
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import json
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import os
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from typing import Dict, List, Tuple
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from src.utils_display import AutoEvalColumn, make_clickable_model
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import numpy as np
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revision: str
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results: dict
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precision: str = "16bit"
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def to_dict(self):
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if self.org is not None:
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data_dict = {}
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data_dict["eval_name"] = self.eval_name # not a column, just a save name
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data_dict[AutoEvalColumn.precision.name] = self.precision
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data_dict[AutoEvalColumn.model.name] = make_clickable_model(base_model)
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data_dict[AutoEvalColumn.dummy.name] = base_model
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data_dict[AutoEvalColumn.revision.name] = self.revision
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continue
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mean_acc = round(np.mean(accs) * 100.0, 1)
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eval_results.append(EvalResult(
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result_key, org, model, model_sha, {benchmark: mean_acc}
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))
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return result_key, eval_results
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def get_eval_results(is_public) -> List[EvalResult]:
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json_filepaths =
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"eval-results/**/results*.json", recursive=True
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)
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if not is_public:
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json_filepaths += glob.glob(
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"private-eval-results/**/results*.json", recursive=True
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)
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-
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for json_filepath in json_filepaths:
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result_key, results = parse_eval_result(json_filepath)
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for eval_result in results:
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def get_eval_results_dicts(is_public=True) -> List[Dict]:
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eval_results = get_eval_results(is_public)
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return [e.to_dict() for e in eval_results]
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import json
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import os
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from typing import Dict, List, Tuple
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import dateutil
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from src.utils_display import AutoEvalColumn, make_clickable_model
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import numpy as np
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revision: str
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results: dict
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precision: str = "16bit"
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model_type: str = ""
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weight_type: str = ""
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def to_dict(self):
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if self.org is not None:
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data_dict = {}
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data_dict["eval_name"] = self.eval_name # not a column, just a save name
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data_dict["weight_type"] = self.weight_type # not a column, just a save name
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data_dict[AutoEvalColumn.precision.name] = self.precision
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data_dict[AutoEvalColumn.model_type.name] = self.model_type
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data_dict[AutoEvalColumn.model.name] = make_clickable_model(base_model)
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data_dict[AutoEvalColumn.dummy.name] = base_model
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data_dict[AutoEvalColumn.revision.name] = self.revision
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continue
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mean_acc = round(np.mean(accs) * 100.0, 1)
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eval_results.append(EvalResult(
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eval_name=result_key, org=org, model=model, revision=model_sha, results={benchmark: mean_acc}, #todo model_type=, weight_type=
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))
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return result_key, eval_results
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def get_eval_results(is_public) -> List[EvalResult]:
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json_filepaths = []
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for root, dir, files in os.walk("eval-results"):
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# We should only have json files in model results
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if len(files) == 0 or any([not f.endswith(".json") for f in files]):
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continue
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# Sort the files by date
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try:
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files.sort(key=lambda x: dateutil.parser.parse(x.split("_", 1)[-1][:-5]))
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except dateutil.parser._parser.ParserError:
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up_to_date = files[-1]
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up_to_date = files[-1]
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if len(files) > 1:
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print(root)
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print(files)
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print(up_to_date)
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print("===")
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json_filepaths.append(os.path.join(root, up_to_date))
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eval_results = {}
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for json_filepath in json_filepaths:
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result_key, results = parse_eval_result(json_filepath)
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for eval_result in results:
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def get_eval_results_dicts(is_public=True) -> List[Dict]:
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eval_results = get_eval_results(is_public)
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return [e.to_dict() for e in eval_results]
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src/auto_leaderboard/model_metadata_type.py
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from enum import Enum
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from typing import Dict, List
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class ModelType(Enum):
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PT = "pretrained"
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SFT = "finetuned"
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RL = "with RL"
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TYPE_METADATA: Dict[str, ModelType] = {
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"aisquared/dlite-v1-355m": ModelType.SFT,
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"aisquared/dlite-v2-774m": ModelType.SFT,
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"aisquared/dlite-v2-1_5b": ModelType.SFT,
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"TheBloke/wizardLM-7B-HF": ModelType.SFT,
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"TheBloke/dromedary-65b-lora-HF": ModelType.SFT,
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"TheBloke/vicuna-13B-1.1-HF": ModelType.SFT,
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"TheBloke/Wizard-Vicuna-13B-Uncensored-HF": ModelType.SFT,
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-
"
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"AlekseyKorshuk/chatml-pyg-v1": ModelType.SFT,
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"concedo/OPT-19M-ChatSalad": ModelType.SFT,
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"digitous/Javalion-R": ModelType.SFT,
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"digitous/Alpacino30b": ModelType.SFT,
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"digitous/Javelin-GPTJ": ModelType.SFT,
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"anton-l/gpt-j-tiny-random": ModelType.SFT,
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"IDEA-CCNL/Ziya-LLaMA-13B-Pretrain-v1": ModelType.SFT,
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"gpt2-medium": ModelType.PT,
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"PygmalionAI/pygmalion-6b": ModelType.SFT,
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"medalpaca/medalpaca-7b": ModelType.SFT,
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-
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"hakurei/lotus-12B": ModelType.SFT,
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"amazon/LightGPT": ModelType.SFT,
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"shibing624/chinese-llama-plus-13b-hf": ModelType.SFT,
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"MetaIX/GPT4-X-Alpasta-30b": ModelType.SFT,
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"EleutherAI/gpt-neox-20b": ModelType.PT,
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"EleutherAI/gpt-j-6b": ModelType.PT,
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"lmsys/vicuna-13b-delta-v1.1": ModelType.SFT,
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"lmsys/vicuna-7b-delta-v1.1": ModelType.SFT,
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"abhiramtirumala/DialoGPT-sarcastic-medium": ModelType.SFT,
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"pillowtalks-ai/delta13b": ModelType.SFT,
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"bigcode/starcoderplus": ModelType.SFT,
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"microsoft/DialoGPT-large": ModelType.SFT,
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|
51 |
"microsoft/CodeGPT-small-py": ModelType.SFT,
|
|
|
52 |
"Pirr/pythia-13b-deduped-green_devil": ModelType.SFT,
|
53 |
"Aeala/GPT4-x-AlpacaDente2-30b": ModelType.SFT,
|
|
|
|
|
54 |
"Aeala/VicUnlocked-alpaca-30b": ModelType.SFT,
|
55 |
-
"
|
|
|
|
|
56 |
"dvruette/oasst-gpt-neox-20b-1000-steps": ModelType.SFT,
|
57 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
58 |
"openlm-research/open_llama_7b_700bt_preview": ModelType.PT,
|
59 |
"openlm-research/open_llama_7b": ModelType.PT,
|
|
|
60 |
"openlm-research/open_llama_3b": ModelType.PT,
|
61 |
-
"openlm-research/
|
|
|
62 |
"PocketDoc/Dans-PileOfSets-Mk1-llama-13b-merged": ModelType.SFT,
|
63 |
-
"GeorgiaTechResearchInstitute/
|
|
|
64 |
"databricks/dolly-v2-7b": ModelType.SFT,
|
65 |
"databricks/dolly-v2-3b": ModelType.SFT,
|
66 |
"databricks/dolly-v2-12b": ModelType.SFT,
|
67 |
-
"pinkmanlove/llama-65b-hf": ModelType.SFT,
|
68 |
"Rachneet/gpt2-xl-alpaca": ModelType.SFT,
|
69 |
"Locutusque/gpt2-conversational-or-qa": ModelType.SFT,
|
|
|
70 |
"NbAiLab/nb-gpt-j-6B-alpaca": ModelType.SFT,
|
|
|
|
|
|
|
|
|
71 |
"Fredithefish/ScarletPajama-3B-HF": ModelType.SFT,
|
|
|
|
|
72 |
"eachadea/vicuna-7b-1.1": ModelType.SFT,
|
73 |
"eachadea/vicuna-13b": ModelType.SFT,
|
74 |
"openaccess-ai-collective/wizard-mega-13b": ModelType.SFT,
|
75 |
"openaccess-ai-collective/manticore-13b": ModelType.SFT,
|
76 |
"openaccess-ai-collective/manticore-30b-chat-pyg-alpha": ModelType.SFT,
|
77 |
"openaccess-ai-collective/minotaur-13b": ModelType.SFT,
|
78 |
-
"
|
|
|
|
|
79 |
"pythainlp/wangchanglm-7.5B-sft-enth": ModelType.SFT,
|
80 |
"pythainlp/wangchanglm-7.5B-sft-en-sharded": ModelType.SFT,
|
|
|
|
|
81 |
"stabilityai/stablelm-tuned-alpha-7b": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
82 |
"CalderaAI/30B-Lazarus": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
83 |
"KoboldAI/OPT-13B-Nerybus-Mix": ModelType.SFT,
|
84 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
85 |
"wahaha1987/llama_7b_sharegpt94k_fastchat": ModelType.SFT,
|
|
|
|
|
|
|
86 |
"OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5": ModelType.SFT,
|
|
|
|
|
|
|
87 |
"junelee/wizard-vicuna-13b": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
|
|
88 |
"BreadAi/StoryPy": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
89 |
"togethercomputer/RedPajama-INCITE-Base-3B-v1": ModelType.PT,
|
|
|
90 |
"togethercomputer/RedPajama-INCITE-Base-7B-v0.1": ModelType.PT,
|
|
|
|
|
|
|
|
|
|
|
91 |
"Writer/camel-5b-hf": ModelType.SFT,
|
92 |
"Writer/palmyra-base": ModelType.PT,
|
|
|
|
|
|
|
|
|
|
|
|
|
93 |
"MBZUAI/lamini-neo-125m": ModelType.SFT,
|
94 |
-
"TehVenom/
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
95 |
"vicgalle/gpt2-alpaca-gpt4": ModelType.SFT,
|
96 |
"facebook/opt-350m": ModelType.PT,
|
97 |
"facebook/opt-125m": ModelType.PT,
|
|
|
|
|
|
|
|
|
98 |
"facebook/opt-13b": ModelType.PT,
|
99 |
-
"facebook/opt-1.3b": ModelType.PT,
|
100 |
"facebook/opt-66b": ModelType.PT,
|
101 |
-
"facebook/
|
102 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
103 |
"gpt2-xl": ModelType.PT,
|
104 |
-
"
|
105 |
-
"
|
106 |
-
"
|
|
|
|
|
|
|
107 |
"HuggingFaceH4/starchat-beta": ModelType.SFT,
|
108 |
-
"
|
|
|
|
|
|
|
|
|
109 |
"ausboss/llama-13b-supercot": ModelType.SFT,
|
110 |
"ausboss/llama-30b-supercot": ModelType.SFT,
|
111 |
"Neko-Institute-of-Science/metharme-7b": ModelType.SFT,
|
|
|
112 |
"SebastianSchramm/Cerebras-GPT-111M-instruction": ModelType.SFT,
|
113 |
"victor123/WizardLM-13B-1.0": ModelType.SFT,
|
114 |
-
"
|
115 |
-
"
|
116 |
"tiiuae/falcon-40b-instruct": ModelType.SFT,
|
117 |
"tiiuae/falcon-40b": ModelType.PT,
|
118 |
"tiiuae/falcon-7b": ModelType.PT,
|
119 |
-
"
|
120 |
-
"
|
|
|
|
|
|
|
121 |
"xzuyn/MedicWizard-7B": ModelType.SFT,
|
122 |
"beomi/KoAlpaca-Polyglot-5.8B": ModelType.SFT,
|
123 |
-
"
|
|
|
124 |
"Salesforce/codegen-16B-nl": ModelType.PT,
|
125 |
-
"Salesforce/codegen-
|
126 |
"ai-forever/rugpt3large_based_on_gpt2": ModelType.SFT,
|
127 |
"gpt2-large": ModelType.PT,
|
|
|
|
|
128 |
"huggingface/llama-13b": ModelType.PT,
|
129 |
"huggingface/llama-7b": ModelType.PT,
|
130 |
"huggingface/llama-65b": ModelType.PT,
|
|
|
131 |
"huggingface/llama-30b": ModelType.PT,
|
132 |
-
"
|
133 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
134 |
"cerebras/Cerebras-GPT-1.3B": ModelType.PT,
|
|
|
|
|
135 |
"cerebras/Cerebras-GPT-111M": ModelType.PT,
|
|
|
|
|
|
|
|
|
|
|
136 |
"NousResearch/Nous-Hermes-13b": ModelType.SFT,
|
137 |
"project-baize/baize-v2-7b": ModelType.SFT,
|
138 |
"project-baize/baize-v2-13b": ModelType.SFT,
|
|
|
139 |
"LLMs/AlpacaGPT4-7B-elina": ModelType.SFT,
|
140 |
-
"
|
|
|
|
|
141 |
"huggingtweets/jerma985": ModelType.SFT,
|
|
|
|
|
|
|
142 |
"huggyllama/llama-65b": ModelType.PT,
|
|
|
|
|
|
|
143 |
"WizardLM/WizardLM-13B-1.0": ModelType.SFT,
|
|
|
|
|
144 |
"gpt2": ModelType.PT,
|
145 |
-
"
|
|
|
|
|
|
|
|
|
146 |
"MayaPH/FinOPT-Lincoln": ModelType.SFT,
|
147 |
"MayaPH/FinOPT-Franklin": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
148 |
"timdettmers/guanaco-33b-merged": ModelType.SFT,
|
149 |
-
"timdettmers/guanaco-65b-merged": ModelType.SFT,
|
150 |
-
"elinas/llama-30b-hf-transformers-4.29": ModelType.SFT,
|
151 |
"elinas/chronos-33b": ModelType.SFT,
|
152 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
153 |
"xhyi/PT_GPTNEO350_ATG": ModelType.SFT,
|
|
|
|
|
|
|
|
|
|
|
|
|
154 |
"h2oai/h2ogpt-oasst1-512-20b": ModelType.SFT,
|
|
|
155 |
"h2oai/h2ogpt-gm-oasst1-en-1024-12b": ModelType.SFT,
|
156 |
-
"
|
157 |
-
"
|
|
|
|
|
|
|
158 |
}
|
159 |
|
160 |
|
161 |
def get_model_type(leaderboard_data: List[dict]):
|
162 |
for model_data in leaderboard_data:
|
163 |
-
|
164 |
-
|
165 |
-
|
166 |
-
|
167 |
-
|
168 |
-
|
169 |
-
|
170 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
171 |
|
172 |
|
|
|
1 |
+
from dataclasses import dataclass
|
2 |
from enum import Enum
|
3 |
from typing import Dict, List
|
4 |
|
5 |
+
from ..utils_display import AutoEvalColumn
|
6 |
+
|
7 |
+
@dataclass
|
8 |
+
class ModelInfo:
|
9 |
+
name: str
|
10 |
+
symbol: str # emoji
|
11 |
+
|
12 |
+
|
13 |
class ModelType(Enum):
|
14 |
+
PT = ModelInfo(name="pretrained", symbol="🟢")
|
15 |
+
SFT = ModelInfo(name="finetuned", symbol="🔶")
|
16 |
+
RL = ModelInfo(name="with RL", symbol="🟦")
|
17 |
|
18 |
|
19 |
TYPE_METADATA: Dict[str, ModelType] = {
|
20 |
+
"notstoic/PygmalionCoT-7b": ModelType.SFT,
|
21 |
"aisquared/dlite-v1-355m": ModelType.SFT,
|
22 |
+
"aisquared/dlite-v1-1_5b": ModelType.SFT,
|
23 |
+
"aisquared/dlite-v1-774m": ModelType.SFT,
|
24 |
+
"aisquared/dlite-v1-124m": ModelType.SFT,
|
25 |
+
"aisquared/chopt-2_7b": ModelType.SFT,
|
26 |
+
"aisquared/dlite-v2-124m": ModelType.SFT,
|
27 |
"aisquared/dlite-v2-774m": ModelType.SFT,
|
28 |
"aisquared/dlite-v2-1_5b": ModelType.SFT,
|
29 |
+
"aisquared/chopt-1_3b": ModelType.SFT,
|
30 |
+
"aisquared/dlite-v2-355m": ModelType.SFT,
|
31 |
+
"TheBloke/tulu-7B-fp16": ModelType.SFT,
|
32 |
+
"TheBloke/guanaco-7B-HF": ModelType.SFT,
|
33 |
+
"TheBloke/koala-7B-HF": ModelType.SFT,
|
34 |
"TheBloke/wizardLM-7B-HF": ModelType.SFT,
|
35 |
+
"TheBloke/airoboros-13B-HF": ModelType.SFT,
|
36 |
+
"TheBloke/koala-13B-HF": ModelType.SFT,
|
37 |
+
"TheBloke/Wizard-Vicuna-7B-Uncensored-HF": ModelType.SFT,
|
38 |
"TheBloke/dromedary-65b-lora-HF": ModelType.SFT,
|
39 |
+
"TheBloke/wizardLM-13B-1.0-fp16": ModelType.SFT,
|
40 |
+
"TheBloke/Wizard-Vicuna-30B-Uncensored-fp16": ModelType.SFT,
|
41 |
+
"TheBloke/wizard-vicuna-13B-HF": ModelType.SFT,
|
42 |
+
"TheBloke/UltraLM-13B-fp16": ModelType.SFT,
|
43 |
+
"TheBloke/OpenAssistant-SFT-7-Llama-30B-HF": ModelType.SFT,
|
44 |
"TheBloke/vicuna-13B-1.1-HF": ModelType.SFT,
|
45 |
+
"TheBloke/guanaco-13B-HF": ModelType.SFT,
|
46 |
+
"TheBloke/airoboros-7b-gpt4-fp16": ModelType.SFT,
|
47 |
+
"TheBloke/Llama-2-13B-fp16": ModelType.PT,
|
48 |
+
"TheBloke/Planner-7B-fp16": ModelType.SFT,
|
49 |
"TheBloke/Wizard-Vicuna-13B-Uncensored-HF": ModelType.SFT,
|
50 |
+
"TheBloke/gpt4-alpaca-lora-13B-HF": ModelType.SFT,
|
51 |
+
"TheBloke/gpt4-x-vicuna-13B-HF": ModelType.SFT,
|
52 |
+
"TheBloke/tulu-13B-fp16": ModelType.SFT,
|
53 |
+
"jphme/orca_mini_v2_ger_7b": ModelType.SFT,
|
54 |
+
"Ejafa/vicuna_7B_vanilla_1.1": ModelType.SFT,
|
55 |
+
"kevinpro/Vicuna-13B-CoT": ModelType.SFT,
|
56 |
+
"AlekseyKorshuk/pygmalion-6b-vicuna-chatml": ModelType.SFT,
|
57 |
"AlekseyKorshuk/chatml-pyg-v1": ModelType.SFT,
|
58 |
+
"concedo/Vicuzard-30B-Uncensored": ModelType.SFT,
|
59 |
"concedo/OPT-19M-ChatSalad": ModelType.SFT,
|
60 |
+
"concedo/Pythia-70M-ChatSalad": ModelType.SFT,
|
61 |
+
"digitous/13B-HyperMantis": ModelType.SFT,
|
62 |
+
"digitous/Adventien-GPTJ": ModelType.SFT,
|
63 |
+
"digitous/Alpacino13b": ModelType.SFT,
|
64 |
+
"digitous/GPT-R": ModelType.SFT,
|
65 |
+
"digitous/Javelin-R": ModelType.SFT,
|
66 |
+
"digitous/Javalion-GPTJ": ModelType.SFT,
|
67 |
"digitous/Javalion-R": ModelType.SFT,
|
68 |
+
"digitous/Skegma-GPTJ": ModelType.SFT,
|
69 |
"digitous/Alpacino30b": ModelType.SFT,
|
70 |
+
"digitous/Janin-GPTJ": ModelType.SFT,
|
71 |
+
"digitous/Janin-R": ModelType.SFT,
|
72 |
"digitous/Javelin-GPTJ": ModelType.SFT,
|
73 |
+
"SaylorTwift/gpt2_test": ModelType.PT,
|
74 |
"anton-l/gpt-j-tiny-random": ModelType.SFT,
|
75 |
+
"Andron00e/YetAnother_Open-Llama-3B-LoRA-OpenOrca": ModelType.SFT,
|
76 |
+
"Lazycuber/pyg-instruct-wizardlm": ModelType.SFT,
|
77 |
+
"Lazycuber/Janemalion-6B": ModelType.SFT,
|
78 |
"IDEA-CCNL/Ziya-LLaMA-13B-Pretrain-v1": ModelType.SFT,
|
79 |
+
"IDEA-CCNL/Ziya-LLaMA-13B-v1": ModelType.SFT,
|
80 |
+
"dsvv-cair/alpaca-cleaned-llama-30b-bf16": ModelType.SFT,
|
81 |
"gpt2-medium": ModelType.PT,
|
82 |
+
"camel-ai/CAMEL-13B-Combined-Data": ModelType.SFT,
|
83 |
+
"camel-ai/CAMEL-13B-Role-Playing-Data": ModelType.SFT,
|
84 |
"PygmalionAI/pygmalion-6b": ModelType.SFT,
|
85 |
+
"PygmalionAI/metharme-1.3b": ModelType.SFT,
|
86 |
+
"PygmalionAI/pygmalion-1.3b": ModelType.SFT,
|
87 |
+
"PygmalionAI/pygmalion-350m": ModelType.SFT,
|
88 |
+
"PygmalionAI/pygmalion-2.7b": ModelType.SFT,
|
89 |
"medalpaca/medalpaca-7b": ModelType.SFT,
|
90 |
+
"lilloukas/Platypus-30B": ModelType.SFT,
|
91 |
+
"lilloukas/GPlatty-30B": ModelType.SFT,
|
92 |
+
"mncai/chatdoctor": ModelType.SFT,
|
93 |
+
"chaoyi-wu/MedLLaMA_13B": ModelType.SFT,
|
94 |
+
"LoupGarou/WizardCoder-Guanaco-15B-V1.0": ModelType.SFT,
|
95 |
+
"LoupGarou/WizardCoder-Guanaco-15B-V1.1": ModelType.SFT,
|
96 |
+
"hakurei/instruct-12b": ModelType.SFT,
|
97 |
"hakurei/lotus-12B": ModelType.SFT,
|
|
|
98 |
"shibing624/chinese-llama-plus-13b-hf": ModelType.SFT,
|
99 |
+
"shibing624/chinese-alpaca-plus-7b-hf": ModelType.SFT,
|
100 |
+
"shibing624/chinese-alpaca-plus-13b-hf": ModelType.SFT,
|
101 |
+
"mosaicml/mpt-7b-instruct": ModelType.SFT,
|
102 |
+
"mosaicml/mpt-30b-chat": ModelType.SFT,
|
103 |
+
"mosaicml/mpt-7b-storywriter": ModelType.SFT,
|
104 |
+
"mosaicml/mpt-30b-instruct": ModelType.SFT,
|
105 |
+
"mosaicml/mpt-7b-chat": ModelType.SFT,
|
106 |
+
"mosaicml/mpt-30b": ModelType.PT,
|
107 |
+
"Corianas/111m": ModelType.SFT,
|
108 |
+
"Corianas/Quokka_1.3b": ModelType.SFT,
|
109 |
+
"Corianas/256_5epoch": ModelType.SFT,
|
110 |
+
"Corianas/Quokka_256m": ModelType.SFT,
|
111 |
+
"Corianas/Quokka_590m": ModelType.SFT,
|
112 |
+
"Corianas/gpt-j-6B-Dolly": ModelType.SFT,
|
113 |
+
"Corianas/Quokka_2.7b": ModelType.SFT,
|
114 |
+
"cyberagent/open-calm-7b": ModelType.SFT,
|
115 |
+
"Aspik101/Nous-Hermes-13b-pl-lora_unload": ModelType.SFT,
|
116 |
+
"THUDM/chatglm2-6b": ModelType.SFT,
|
117 |
"MetaIX/GPT4-X-Alpasta-30b": ModelType.SFT,
|
118 |
+
"NYTK/PULI-GPTrio": ModelType.PT,
|
119 |
+
"EleutherAI/pythia-1.3b": ModelType.PT,
|
120 |
+
"EleutherAI/pythia-2.8b-deduped": ModelType.PT,
|
121 |
+
"EleutherAI/gpt-neo-125m": ModelType.PT,
|
122 |
+
"EleutherAI/pythia-160m": ModelType.PT,
|
123 |
+
"EleutherAI/gpt-neo-2.7B": ModelType.PT,
|
124 |
+
"EleutherAI/pythia-1b-deduped": ModelType.PT,
|
125 |
+
"EleutherAI/pythia-6.7b": ModelType.PT,
|
126 |
+
"EleutherAI/pythia-70m-deduped": ModelType.PT,
|
127 |
"EleutherAI/gpt-neox-20b": ModelType.PT,
|
128 |
+
"EleutherAI/pythia-1.4b-deduped": ModelType.PT,
|
129 |
+
"EleutherAI/pythia-2.7b": ModelType.PT,
|
130 |
+
"EleutherAI/pythia-6.9b-deduped": ModelType.PT,
|
131 |
+
"EleutherAI/pythia-70m": ModelType.PT,
|
132 |
"EleutherAI/gpt-j-6b": ModelType.PT,
|
133 |
+
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+
"Salesforce/codegen-6B-multi": ModelType.PT,
|
376 |
"Salesforce/codegen-16B-nl": ModelType.PT,
|
377 |
+
"Salesforce/codegen-6B-nl": ModelType.PT,
|
378 |
"ai-forever/rugpt3large_based_on_gpt2": ModelType.SFT,
|
379 |
"gpt2-large": ModelType.PT,
|
380 |
+
"frank098/orca_mini_3b_juniper": ModelType.SFT,
|
381 |
+
"frank098/WizardLM_13B_juniper": ModelType.SFT,
|
382 |
"huggingface/llama-13b": ModelType.PT,
|
383 |
"huggingface/llama-7b": ModelType.PT,
|
384 |
"huggingface/llama-65b": ModelType.PT,
|
385 |
+
"huggingface/llama-65b": ModelType.PT,
|
386 |
"huggingface/llama-30b": ModelType.PT,
|
387 |
+
"jondurbiModelType.iroboros-13b-gpt4-1.4": ModelType.SFT,
|
388 |
+
"jondurbiModelType.iroboros-7b": ModelType.SFT,
|
389 |
+
"jondurbiModelType.iroboros-7b-gpt4-1.4": ModelType.SFT,
|
390 |
+
"jondurbiModelType.iroboros-l2-13b-gpt4-1.4.1": ModelType.SFT,
|
391 |
+
"jondurbiModelType.iroboros-13b": ModelType.SFT,
|
392 |
+
"ariellee/SuperPlatty-30B": ModelType.SFT,
|
393 |
+
"danielhanchen/open_llama_3b_600bt_preview": ModelType.SFT,
|
394 |
+
"cerebras/Cerebras-GPT-256M": ModelType.PT,
|
395 |
"cerebras/Cerebras-GPT-1.3B": ModelType.PT,
|
396 |
+
"cerebras/Cerebras-GPT-13B": ModelType.PT,
|
397 |
+
"cerebras/Cerebras-GPT-2.7B": ModelType.PT,
|
398 |
"cerebras/Cerebras-GPT-111M": ModelType.PT,
|
399 |
+
"cerebras/Cerebras-GPT-6.7B": ModelType.PT,
|
400 |
+
"Yhyu13/oasst-rlhf-2-llama-30b-7k-steps-hf": ModelType.RL,
|
401 |
+
"Yhyu13/llama-30B-hf-openassitant": ModelType.SFT,
|
402 |
+
"NousResearch/Nous-Hermes-Llama2-13b": ModelType.SFT,
|
403 |
+
"NousResearch/Redmond-Puffin-13B": ModelType.SFT,
|
404 |
"NousResearch/Nous-Hermes-13b": ModelType.SFT,
|
405 |
"project-baize/baize-v2-7b": ModelType.SFT,
|
406 |
"project-baize/baize-v2-13b": ModelType.SFT,
|
407 |
+
"LLMs/WizardLM-13B-V1.0": ModelType.SFT,
|
408 |
"LLMs/AlpacaGPT4-7B-elina": ModelType.SFT,
|
409 |
+
"wenge-research/yayi-7b-llama2": ModelType.SFT,
|
410 |
+
"yhyhy3/open_llama_7b_v2_med_instruct": ModelType.SFT,
|
411 |
+
"llama-anon/instruct-13b": ModelType.SFT,
|
412 |
"huggingtweets/jerma985": ModelType.SFT,
|
413 |
+
"huggingtweets/gladosystem": ModelType.SFT,
|
414 |
+
"huggingtweets/bladeecity-jerma985": ModelType.SFT,
|
415 |
+
"huggyllama/llama-13b": ModelType.PT,
|
416 |
"huggyllama/llama-65b": ModelType.PT,
|
417 |
+
"FabbriSimo01/Facebook_opt_1.3b_Quantized": ModelType.PT,
|
418 |
+
"upstage/llama-30b-instruct-2048": ModelType.SFT,
|
419 |
+
"upstage/llama-30b-instruct": ModelType.SFT,
|
420 |
"WizardLM/WizardLM-13B-1.0": ModelType.SFT,
|
421 |
+
"WizardLM/WizardLM-30B-V1.0": ModelType.SFT,
|
422 |
+
"WizardLM/WizardCoder-15B-V1.0": ModelType.SFT,
|
423 |
"gpt2": ModelType.PT,
|
424 |
+
"keyfan/vicuna-chinese-replication-v1.1": ModelType.SFT,
|
425 |
+
"nthngdy/pythia-owt2-70m-100k": ModelType.SFT,
|
426 |
+
"nthngdy/pythia-owt2-70m-50k": ModelType.SFT,
|
427 |
+
"quantumaikr/KoreanLM-hf": ModelType.SFT,
|
428 |
+
"quantumaikr/open_llama_7b_hf": ModelType.SFT,
|
429 |
"MayaPH/FinOPT-Lincoln": ModelType.SFT,
|
430 |
"MayaPH/FinOPT-Franklin": ModelType.SFT,
|
431 |
+
"MayaPH/GodziLLa-30B": ModelType.SFT,
|
432 |
+
"MayaPH/FinOPT-Washington": ModelType.SFT,
|
433 |
+
"ogimgio/gpt-neo-125m-neurallinguisticpioneers": ModelType.SFT,
|
434 |
+
"layoric/llama-2-13b-code-alpaca": ModelType.SFT,
|
435 |
+
"CobraMamba/mamba-gpt-3b": ModelType.SFT,
|
436 |
"timdettmers/guanaco-33b-merged": ModelType.SFT,
|
|
|
|
|
437 |
"elinas/chronos-33b": ModelType.SFT,
|
438 |
+
"heegyu/RedTulu-Uncensored-3B-0719": ModelType.SFT,
|
439 |
+
"heegyu/WizardVicuna-Uncensored-3B-0719": ModelType.SFT,
|
440 |
+
"heegyu/WizardVicuna-3B-0719": ModelType.SFT,
|
441 |
+
"meta-llama/Llama-2-7b-chat-hf": ModelType.RL,
|
442 |
+
"meta-llama/Llama-2-7b-hf": ModelType.PT,
|
443 |
+
"meta-llama/Llama-2-13b-chat-hf": ModelType.RL,
|
444 |
+
"meta-llama/Llama-2-13b-hf": ModelType.PT,
|
445 |
+
"meta-llama/Llama-2-70b-chat-hf": ModelType.RL,
|
446 |
+
"meta-llama/Llama-2-70b-hf": ModelType.PT,
|
447 |
"xhyi/PT_GPTNEO350_ATG": ModelType.SFT,
|
448 |
+
"h2oai/h2ogpt-gm-oasst1-en-1024-20b": ModelType.SFT,
|
449 |
+
"h2oai/h2ogpt-gm-oasst1-en-1024-open-llama-7b-preview-400bt": ModelType.SFT,
|
450 |
+
"h2oai/h2ogpt-oig-oasst1-512-6_9b": ModelType.SFT,
|
451 |
+
"h2oai/h2ogpt-oasst1-512-12b": ModelType.SFT,
|
452 |
+
"h2oai/h2ogpt-oig-oasst1-256-6_9b": ModelType.SFT,
|
453 |
+
"h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b-preview-300bt": ModelType.SFT,
|
454 |
"h2oai/h2ogpt-oasst1-512-20b": ModelType.SFT,
|
455 |
+
"h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b-preview-300bt-v2": ModelType.SFT,
|
456 |
"h2oai/h2ogpt-gm-oasst1-en-1024-12b": ModelType.SFT,
|
457 |
+
"h2oai/h2ogpt-gm-oasst1-multilang-1024-20b": ModelType.SFT,
|
458 |
+
"bofenghuang/vigogne-13b-instruct": ModelType.SFT,
|
459 |
+
"Vmware/open-llama-7b-v2-open-instruct": ModelType.SFT,
|
460 |
+
"VMware/open-llama-0.7T-7B-open-instruct-v1.1": ModelType.SFT,
|
461 |
+
"ewof/koishi-instruct-3b": ModelType.SFT,
|
462 |
}
|
463 |
|
464 |
|
465 |
def get_model_type(leaderboard_data: List[dict]):
|
466 |
for model_data in leaderboard_data:
|
467 |
+
# Todo @clefourrier once requests are connected with results
|
468 |
+
is_delta = False # (model_data["weight_type"] != "Original")
|
469 |
+
# Stored information
|
470 |
+
if model_data["model_name_for_query"] in TYPE_METADATA:
|
471 |
+
model_data[AutoEvalColumn.model_type.name] = TYPE_METADATA[model_data["model_name_for_query"]].value.name
|
472 |
+
model_data[AutoEvalColumn.model_type_symbol.name] = TYPE_METADATA[model_data["model_name_for_query"]].value.symbol + ("🔺" if is_delta else "")
|
473 |
+
# Inferred from the name or the selected type
|
474 |
+
elif model_data[AutoEvalColumn.model_type.name] == "pretrained" or any([i in model_data["model_name_for_query"] for i in ["pretrained"]]):
|
475 |
+
model_data[AutoEvalColumn.model_type.name] = ModelType.PT.value.name
|
476 |
+
model_data[AutoEvalColumn.model_type_symbol.name] = ModelType.PT.value.symbol + ("🔺" if is_delta else "")
|
477 |
+
elif model_data[AutoEvalColumn.model_type.name] == "finetuned" or any([i in model_data["model_name_for_query"] for i in ["finetuned", "-ft-"]]):
|
478 |
+
model_data[AutoEvalColumn.model_type.name] = ModelType.SFT.value.name
|
479 |
+
model_data[AutoEvalColumn.model_type_symbol.name] = ModelType.SFT.value.symbol + ("🔺" if is_delta else "")
|
480 |
+
elif model_data[AutoEvalColumn.model_type.name] == "with RL" or any([i in model_data["model_name_for_query"] for i in ["-rl-", "-rlhf-"]]):
|
481 |
+
model_data[AutoEvalColumn.model_type.name] = ModelType.RL.value.name
|
482 |
+
model_data[AutoEvalColumn.model_type_symbol.name] = ModelType.RL.value.symbol + ("🔺" if is_delta else "")
|
483 |
+
else:
|
484 |
+
model_data[AutoEvalColumn.model_type.name] = "N/A"
|
485 |
+
model_data[AutoEvalColumn.model_type_symbol.name] = ("🔺" if is_delta else "")
|
486 |
|
487 |
|
src/init.py
CHANGED
File without changes
|
src/utils_display.py
CHANGED
@@ -14,12 +14,13 @@ def fields(raw_class):
|
|
14 |
|
15 |
@dataclass(frozen=True)
|
16 |
class AutoEvalColumn: # Auto evals column
|
|
|
17 |
model = ColumnContent("Model", "markdown", True)
|
18 |
average = ColumnContent("Average ⬆️", "number", True)
|
19 |
-
arc = ColumnContent("ARC
|
20 |
-
hellaswag = ColumnContent("HellaSwag
|
21 |
-
mmlu = ColumnContent("MMLU
|
22 |
-
truthfulqa = ColumnContent("TruthfulQA
|
23 |
model_type = ColumnContent("Type", "str", False)
|
24 |
precision = ColumnContent("Precision", "str", False, True)
|
25 |
license = ColumnContent("Hub License", "str", False)
|
|
|
14 |
|
15 |
@dataclass(frozen=True)
|
16 |
class AutoEvalColumn: # Auto evals column
|
17 |
+
model_type_symbol = ColumnContent("T", "str", True)
|
18 |
model = ColumnContent("Model", "markdown", True)
|
19 |
average = ColumnContent("Average ⬆️", "number", True)
|
20 |
+
arc = ColumnContent("ARC", "number", True)
|
21 |
+
hellaswag = ColumnContent("HellaSwag", "number", True)
|
22 |
+
mmlu = ColumnContent("MMLU", "number", True)
|
23 |
+
truthfulqa = ColumnContent("TruthfulQA", "number", True)
|
24 |
model_type = ColumnContent("Type", "str", False)
|
25 |
precision = ColumnContent("Precision", "str", False, True)
|
26 |
license = ColumnContent("Hub License", "str", False)
|