| | --- |
| | tags: |
| | - sparse sparsity quantized onnx embeddings int8 |
| | license: mit |
| | language: |
| | - en |
| | --- |
| | |
| | # gte-base-sparse |
| |
|
| | This is the sparse ONNX variant of the [gte-base](https://huggingface.co/thenlper/gte-base) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization (INT8) and unstructured pruning 50%. |
| |
|
| | Current list of sparse and quantized gte ONNX models: |
| |
|
| | | Links | Sparsification Method | |
| | | --------------------------------------------------------------------------------------------------- | ---------------------- | |
| | | [zeroshot/gte-large-sparse](https://huggingface.co/zeroshot/gte-large-sparse) | Quantization (INT8) & 50% Pruning | |
| | | [zeroshot/gte-large-quant](https://huggingface.co/zeroshot/gte-large-quant) | Quantization (INT8) | |
| | | [zeroshot/gte-base-sparse](https://huggingface.co/zeroshot/gte-base-sparse) | Quantization (INT8) & 50% Pruning | |
| | | [zeroshot/gte-base-quant](https://huggingface.co/zeroshot/gte-base-quant) | Quantization (INT8) | |
| | | [zeroshot/gte-small-sparse](https://huggingface.co/zeroshot/gte-small-sparse) | Quantization (INT8) & 50% Pruning | |
| | | [zeroshot/gte-small-quant](https://huggingface.co/zeroshot/gte-small-quant) | Quantization (INT8) | |
| |
|
| | ```bash |
| | pip install -U deepsparse-nightly[sentence_transformers] |
| | ``` |
| |
|
| | ```python |
| | from deepsparse.sentence_transformers import SentenceTransformer |
| | model = SentenceTransformer('zeroshot/gte-base-sparse', export=False) |
| | |
| | # Our sentences we like to encode |
| | sentences = ['This framework generates embeddings for each input sentence', |
| | 'Sentences are passed as a list of string.', |
| | 'The quick brown fox jumps over the lazy dog.'] |
| | |
| | # Sentences are encoded by calling model.encode() |
| | embeddings = model.encode(sentences) |
| | |
| | # Print the embeddings |
| | for sentence, embedding in zip(sentences, embeddings): |
| | print("Sentence:", sentence) |
| | print("Embedding:", embedding.shape) |
| | print("") |
| | ``` |
| |
|
| | For further details regarding DeepSparse & Sentence Transformers integration, refer to the [DeepSparse README](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/sentence_transformers). |
| |
|
| | For general questions on these models and sparsification methods, reach out to the engineering team on our [community Slack](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ). |
| |
|
| |  |
| |
|
| |
|
