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Update README.md
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README.md
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@@ -127,10 +127,10 @@ marqo-gs-dataset/
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βββ marqo_gs_wfash_1m/
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```
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For each dataset such as marqo_gs_full_10m, there are 4 splits as discussed before.
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- query_0_product_id_0 represents in-domain set,
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- query_1_product_id_0 represents novel query set,
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- query_0_product_id_1 represents novel document set,
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- query_1_product_id_1 represents zero shot set,
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For each split, there is a ground truth csv containing triplet information,
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a set of validation ground truth and a set of test ground truth.
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@@ -250,7 +250,7 @@ with torch.no_grad(), torch.cuda.amp.autocast():
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print("Label probs:", text_probs)
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```
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### Quick Demo with Hugging Face for E5 models.
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Here is a quick example to load our finetuned e5 text models from
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```python
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import torch.nn.functional as F
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βββ marqo_gs_wfash_1m/
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```
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For each dataset such as marqo_gs_full_10m, there are 4 splits as discussed before.
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+
- `query_0_product_id_0` represents in-domain set,
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+
- `query_1_product_id_0` represents novel query set,
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+
- `query_0_product_id_1` represents novel document set,
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+
- `query_1_product_id_1` represents zero shot set,
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For each split, there is a ground truth csv containing triplet information,
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a set of validation ground truth and a set of test ground truth.
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print("Label probs:", text_probs)
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```
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### Quick Demo with Hugging Face for E5 models.
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Here is a quick example to load our finetuned e5 text models from Hugging Face directly.
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```python
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import torch.nn.functional as F
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