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from huggingface_hub import HfApi, Repository
def restart_space(LLM_PERF_LEADERBOARD_REPO, OPTIMUM_TOKEN):
HfApi().restart_space(
repo_id=LLM_PERF_LEADERBOARD_REPO, token=OPTIMUM_TOKEN
)
def load_dataset_repo(LLM_PERF_DATASET_REPO, OPTIMUM_TOKEN):
llm_perf_repo = None
if OPTIMUM_TOKEN:
print("Loading LLM-Perf-Dataset from Hub...")
llm_perf_repo = Repository(
local_dir="./llm-perf/",
clone_from=LLM_PERF_DATASET_REPO,
token=OPTIMUM_TOKEN,
repo_type="dataset",
)
llm_perf_repo.git_pull()
return llm_perf_repo
LLAMAS = ["huggingface/llama-7b", "huggingface/llama-13b",
"huggingface/llama-30b", "huggingface/llama-65b"]
KOALA_LINK = "https://huggingface.co/TheBloke/koala-13B-HF"
VICUNA_LINK = "https://huggingface.co/lmsys/vicuna-13b-delta-v1.1"
OASST_LINK = "https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5"
DOLLY_LINK = "https://huggingface.co/databricks/dolly-v2-12b"
MODEL_PAGE = "https://huggingface.co/models"
LLAMA_LINK = "https://ai.facebook.com/blog/large-language-model-llama-meta-ai/"
VICUNA_LINK = "https://huggingface.co/CarperAI/stable-vicuna-13b-delta"
ALPACA_LINK = "https://crfm.stanford.edu/2023/03/13/alpaca.html"
def model_hyperlink(link, model_name):
return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
def make_clickable_model(model_name):
link = f"https://huggingface.co/{model_name}"
if model_name in LLAMAS:
link = LLAMA_LINK
model_name = model_name.split("/")[1]
elif model_name == "HuggingFaceH4/stable-vicuna-13b-2904":
link = VICUNA_LINK
model_name = "stable-vicuna-13b"
elif model_name == "HuggingFaceH4/llama-7b-ift-alpaca":
link = ALPACA_LINK
model_name = "alpaca-13b"
if model_name == "dolly-12b":
link = DOLLY_LINK
elif model_name == "vicuna-13b":
link = VICUNA_LINK
elif model_name == "koala-13b":
link = KOALA_LINK
elif model_name == "oasst-12b":
link = OASST_LINK
return model_hyperlink(link, model_name)
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