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from dataclasses import dataclass | |
from enum import Enum | |
class Task: | |
benchmark: str | |
metric: str | |
col_name: str | |
# Select your tasks here | |
# --------------------------------------------------- | |
class Tasks(Enum): | |
# task_key in the json file, metric_key in the json file, name to display in the leaderboard | |
task0 = Task("mmlu_it", "acc", "MMLU_IT") | |
task1 = Task("arc_it", "acc_norm", "ARC_IT") | |
task2 = Task("hellaswag_it", "acc_norm", "HELLASWAG_IT") | |
NUM_FEWSHOT = 0 # Change with your few shot | |
# --------------------------------------------------- | |
# Your leaderboard name | |
TITLE = """<h1 align="center" id="space-title">🚀 Classifica generale degli LLM italiani 🚀</h1>""" | |
# What does your leaderboard evaluate? | |
INTRODUCTION_TEXT = """ | |
Benvenuti nella pagina della open ita llm leaderboard! | |
In questa dashboard potrete trovare tutti i risultati delle performance dei Large Language Models nella lingua italiana sui principali eval effettuati grazie al fantastico [Eleuther AI Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) | |
Maggiori info nella sezione "about" | |
P.s. la classifica è 100% open source, chiunque può contribuire e aggiungere il proprio modello tramite questo [form](https://forms.gle/Gc9Dfu52xSBhQPpAA) nel mentre che la submission automatica sarà operativa :) | |
Se avete idee/miglioramenti/suggerimenti [scrivetemi pure](https://www.linkedin.com/in/samuele-colombo-ml/) oppure mi trovate sul [discord della community](https://discord.gg/kc97Zwc4ze) | |
""" | |
# Which evaluations are you running? how can people reproduce what you have? | |
LLM_BENCHMARKS_TEXT = f""" | |
## Come funziona | |
Valutiamo i modelli tramite <a href="https://github.com/EleutherAI/lm-evaluation-harness" target="_blank"> Eleuther AI Language Model Evaluation Harness </a>, il framework più utilizzato dalla community internazionale per l'evaluation dei modelli | |
Nella classifica troverete i dataset di benchmark più famosi, adatti alla lingua italiana. I task sono: | |
- <a href="https://huggingface.co/datasets/alexandrainst/m_hellaswag" target="_blank"> hellaswag_it </a> | |
- <a href="https://huggingface.co/datasets/alexandrainst/m_arc" target="_blank"> arc_it </a> | |
- <a href="https://huggingface.co/datasets/alexandrainst/m_mmlu" target="_blank"> m_mmlu_it </a> (5 shots) | |
Per tutti questi task, a un punteggio migliore corrisponde una performance maggiore | |
## Reproducibility | |
Per riprodurre i risultati scaricate la <a href="https://github.com/EleutherAI/lm-evaluation-harness" target="_blank"> Eleuther AI Language Model Evaluation Harness </a> ed eseguite: | |
* lm-eval --model hf --model_args pretrained=<vostro modello> --tasks hellaswag_it,arc_it --device cuda:0 --batch_size auto:2; | |
* lm-eval --model hf --model_args pretrained=<vostro modello>, --tasks m_mmlu_it --num_fewshot 5 --device cuda:0 --batch_size auto:2 | |
""" | |
EVALUATION_QUEUE_TEXT = """ | |
## Some good practices before submitting a model | |
### 1) Make sure you can load your model and tokenizer using AutoClasses: | |
```python | |
from transformers import AutoConfig, AutoModel, AutoTokenizer | |
config = AutoConfig.from_pretrained("your model name", revision=revision) | |
model = AutoModel.from_pretrained("your model name", revision=revision) | |
tokenizer = AutoTokenizer.from_pretrained("your model name", revision=revision) | |
``` | |
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! | |
Note: if your model needs `use_remote_code=True`, we do not support this option yet but we are working on adding it, stay posted! | |
### 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""" | |
Paper coming soon! | |
Pls dateci credits se usate i nostri benchmarks :) | |
""" | |