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
File size: 435 Bytes
0e37bb2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # 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
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