Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use kurier-digital/geronimo-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kurier-digital/geronimo-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kurier-digital/geronimo-base") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use kurier-digital/geronimo-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kurier-digital/geronimo-base") model = AutoModel.from_pretrained("kurier-digital/geronimo-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add exported ONNX model 'model_qint8_avx512_vnni.onnx'
Verified signatureHello! *This pull request has been automatically generated from the [`export_dynamic_quantized_onnx_model`](https://sbert.net/docs/package_reference/util.html#sentence_transformers.backend.export_dynamic_quantized_onnx_model) function from the Sentence Transformers library.* ## Config ```python QuantizationConfig( is_static=False, format=<QuantFormat.QOperator: 0>, mode=<QuantizationMode.IntegerOps: 0>, activations_dtype=<QuantType.QUInt8: 1>, activations_symmetric=False, weights_dtype=<QuantType.QInt8: 0>, weights_symmetric=True, per_channel=True, reduce_range=False, nodes_to_quantize=[], nodes_to_exclude=[], operators_to_quantize=['Conv', 'MatMul', 'Attention', 'LSTM', 'Gather', 'Transpose', 'EmbedLayerNormalization'], qdq_add_pair_to_weight=False, qdq_dedicated_pair=False, qdq_op_type_per_channel_support_to_axis={'MatMul': 1} ) ``` ## Tip: Consider testing this pull request before merging by loading the model from this PR with the `revision` argument: ```pyth…12812f7
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finetuned qa dataset 6 epochs
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finetuned qa dataset 4 epochs
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finetuned sts dataset 4 epochs
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Add new SentenceTransformer model.
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initial commit
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