Feature Extraction
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Gutema/Last_BERT_V2")
model = AutoModel.from_pretrained("Gutema/Last_BERT_V2", device_map="auto")Quick Links
Last_BERT_V2
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 4.40.0
- TensorFlow 2.15.0
- Tokenizers 0.19.1
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Gutema/Last_BERT_V2")