# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-rembert")
model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-rembert")Quick Links
tiny-random-rembert
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.18.0.dev0
- TensorFlow 2.7.0
- Datasets 1.18.3
- Tokenizers 0.11.0
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-rembert")