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from dataclasses import dataclass | |
from enum import Enum | |
class Task: | |
benchmark: str | |
metric: str | |
col_name: str | |
# Init: to update with your specific keys | |
class Tasks(Enum): | |
# task_key in the json file, metric_key in the json file, name to display in the leaderboard | |
task0 = Task("task_name1", "metric_name", "First task") | |
task1 = Task("task_name2", "metric_name", "Second task") | |
# Init: to update with your specific keys | |
#class Tasks(Enum): | |
# # task_key in the json file, metric_key in the json file, name to display in the leaderboard | |
# task0 = Task("logiqa", "delta_abs", "LogiQA Δ") | |
# task1 = Task("logiqa2", "delta_abs", "LogiQA2 Δ") | |
#METRICS = list(set([task.value.metric for task in Tasks])) | |
# Your leaderboard name | |
TITLE = """<h1 align="center" id="space-title">Open CoT Leaderboard</h1>""" | |
# What does your leaderboard evaluate? | |
INTRODUCTION_TEXT = """ | |
Intro text | |
""" | |
# Which evaluations are you running? how can people reproduce what you have? | |
LLM_BENCHMARKS_TEXT = f""" | |
## How it works | |
## Reproducibility | |
To reproduce our results, here is the commands you can run: | |
""" | |
EVALUATION_QUEUE_TEXT = """ | |
## Some good practices before submitting a model | |
### 1) Make sure you can load your model and tokenizer with `vLLM`: | |
```python | |
from vllm import LLM, SamplingParams | |
prompts = [ | |
"Hello, my name is", | |
"The president of the United States is", | |
"The capital of France is", | |
"The future of AI is", | |
] | |
sampling_params = SamplingParams(temperature=0.8, top_p=0.95) | |
llm = LLM(model="<USER>/<MODEL>") | |
outputs = llm.generate(prompts, sampling_params) | |
``` | |
If this step fails, follow the error messages to debug your model before submitting it. It's likely your model has been improperly uploaded. | |
Note: make sure your model is public! | |
### 2) Convert your model weights to [safetensors](https://huggingface.co/docs/safetensors/index) | |
It's a new format for storing weights which is safer and faster to load and use. It will also allow us to add the number of parameters of your model to the `Extended Viewer`! | |
### 3) Make sure your model has an open license! | |
This is a leaderboard for Open LLMs, and we'd love for as many people as possible to know they can use your model 🤗 | |
### 4) Fill up your model card | |
When we add extra information about models to the leaderboard, it will be automatically taken from the model card | |
## In case of model failure | |
If your model is displayed in the `FAILED` category, its execution stopped. | |
Make sure you have followed the above steps first. | |
If everything is done, check you can launch the EleutherAIHarness on your model locally, using the above command without modifications (you can add `--limit` to limit the number of examples per task). | |
""" | |
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results" | |
CITATION_BUTTON_TEXT = r""" | |
""" | |