Sentence Similarity
Transformers
PyTorch
English
bert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use dwzhu/e5-base-4k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dwzhu/e5-base-4k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dwzhu/e5-base-4k") model = AutoModel.from_pretrained("dwzhu/e5-base-4k") - Inference
- Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
#2
by RajSang - opened
- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -52,7 +52,7 @@
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| 52 |
"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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| 55 |
-
"model_max_length":
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| 56 |
"pad_token": "[PAD]",
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| 57 |
"sep_token": "[SEP]",
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| 58 |
"strip_accents": null,
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| 52 |
"cls_token": "[CLS]",
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| 53 |
"do_lower_case": true,
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| 54 |
"mask_token": "[MASK]",
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| 55 |
+
"model_max_length": 4096,
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| 56 |
"pad_token": "[PAD]",
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| 57 |
"sep_token": "[SEP]",
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| 58 |
"strip_accents": null,
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