Update README.md

README.md

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 This is the sparse ONNX variant of the [gte-small](https://huggingface.co/thenlper/gte-small) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export 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-small ONNX models:
+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)                     |
 
-BGE models using this architecture:
-
-| Links                                                                                               | Sparsification Method |
-| --------------------------------------------------------------------------------------------------- | ---------------------- |
-| [zeroshot/bge-large-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-large-en-v1.5-sparse)     |    Quantization (INT8) & 50% Pruning                    |
-| [zeroshot/bge-large-en-v1.5-quant](https://huggingface.co/zeroshot/bge-large-en-v1.5-quant)     |   Quantization (INT8)                     |
-| [zeroshot/bge-base-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-base-en-v1.5-sparse)     |   Quantization (INT8) & 50% Pruning                     |
-| [zeroshot/bge-base-en-v1.5-quant](https://huggingface.co/zeroshot/bge-base-en-v1.5-quant)     |     Quantization (INT8)                    |
-| [zeroshot/bge-small-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-small-en-v1.5-sparse) |    Quantization (INT8) & 50% Pruning                    |
-| [zeroshot/bge-small-en-v1.5-quant](https://huggingface.co/zeroshot/bge-small-en-v1.5-quant) |     Quantization (INT8)                    |
 
 
 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).