Alex Friedmann
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Upload 7 files
Browse files- .gitattributes +1 -0
- README.md +26 -3
- config.json +28 -0
- model.onnx +3 -0
- ort_config.json +35 -0
- special_tokens_map.json +51 -0
- tokenizer.json +3 -0
- tokenizer_config.json +55 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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-
---
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license: mit
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---
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---
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license: mit
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---
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Converted [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) model (dense retriever only) in onnx int8 format for use with [Vespa Embedding](https://docs.vespa.ai/en/embedding.html).
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- BAAI-bge-m3_quantized.onnx (int8 quantized)
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The model was quantized using the [optimum](https://github.com/huggingface/optimum) toolkit.
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## Tips: conver to int8 quantized
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```
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# https://github.com/vespa-engine/sample-apps/blob/master/simple-semantic-search/export_hf_model_from_hf.py
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./export_hf_model_from_hf.py --hf_model BAAI/bge-m3 --output_dir bge-m3
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```
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```
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optimum-cli onnxruntime quantize --onnx_model ./bge-m3 -o bge-m3-large_quantized --avx512_vnni
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```
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## License
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The license for this model is based on the original license (found in the LICENSE file in the project's root directory), which is the MIT License.
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- https://huggingface.co/BAAI/bge-m3
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## Attribution
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All credits for this model go to the authors of BAAI/bge-m3 and the associated researchers and organizations. When using this model, please be sure to attribute the original authors.
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config.json
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{
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"_name_or_path": "m3",
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"architectures": [
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"XLMRobertaModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 8194,
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"model_type": "xlm-roberta",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:796e1f3985226cb8e5b3b52f9c70154c82ab3d65cfed13fdf6faea03aae67cd3
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size 569721516
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ort_config.json
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{
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"one_external_file": true,
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"opset": null,
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"optimization": {},
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"optimum_version": "1.17.1",
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"quantization": {
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"activations_dtype": "QUInt8",
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"activations_symmetric": false,
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"format": "QOperator",
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"is_static": false,
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"mode": "IntegerOps",
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"nodes_to_exclude": [],
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"nodes_to_quantize": [],
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"operators_to_quantize": [
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"Conv",
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"MatMul",
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"Attention",
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"LSTM",
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"Gather",
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"Transpose",
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"EmbedLayerNormalization"
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],
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"per_channel": false,
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"qdq_add_pair_to_weight": false,
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"qdq_dedicated_pair": false,
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"qdq_op_type_per_channel_support_to_axis": {
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"MatMul": 1
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},
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"reduce_range": false,
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"weights_dtype": "QInt8",
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"weights_symmetric": true
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},
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"transformers_version": "4.35.2",
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"use_external_data_format": false
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}
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"single_word": false
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},
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"cls_token": {
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"content": "<s>",
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": true,
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"lstrip": false,
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"unk_token": {
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:6710678b12670bc442b99edc952c4d996ae309a7020c1fa0096dd245c2faf790
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size 17082821
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tokenizer_config.json
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"sp_model_kwargs": {},
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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