license: mit datasets:
- openai/MMMLU
- argilla/FinePersonas-v0.1
- SkunkworksAI/reasoning-0.01
- fka/awesome-chatgpt-prompts metrics:
- accuracy
- bleu
- bertscore
- bleurt base_model:
- meta-llama/Llama-3.2-11B-Vision-Instruct
- nvidia/NVLM-D-72B
- openai/whisper-large-v3-turbo new_version: meta-llama/Llama-3.1-8B-Instruct pipeline_tag: question-answering library_name: adapter-transformers
from transformers import AutoModelForQuestionAnswering, Trainer, TrainingArguments model = AutoModelForQuestionAnswering.from_pretrained("your-model-name")
pip install transformers datasets
training_args = TrainingArguments( output_dir='./results', num_train_epochs=3, per_device_train_batch_size=16, evaluation_strategy="epoch" )
---eval_results = trainer.evaluate() print(eval_results)