Video-Text-to-Text
Transformers
Safetensors
English
soccer_qa_4b
soccer
video-qa
question-answering
vision-language
multimodal
sports-analysis
Instructions to use sportsvision/soccer-qa-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sportsvision/soccer-qa-4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sportsvision/soccer-qa-4b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| from logging import getLogger | |
| import torch | |
| _GLOBAL_SEED = 0 | |
| logger = getLogger() | |
| class DefaultCollator(object): | |
| def __call__(self, batch): | |
| collated_batch = torch.utils.data.default_collate(batch) | |
| return collated_batch, None, None | |