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Add new ColBERT model

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Files changed (4) hide show
  1. 2_Dense/config.json +7 -0
  2. 2_Dense/model.safetensors +3 -0
  3. README.md +3 -2
  4. modules.json +6 -0
2_Dense/config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
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+ {
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+ "in_features": 128,
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+ "out_features": 768,
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+ "bias": false,
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+ "activation_function": "torch.nn.modules.linear.Identity",
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+ "use_residual": false
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+ }
2_Dense/model.safetensors ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:1b9aa25fbcb8a9175185ee625fa7d0460cf409797116efe226b55473c8e034ba
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+ size 196696
README.md CHANGED
@@ -24,7 +24,7 @@ library_name: PyLate
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  # Redis fine-tuned late-interaction ColBERT model for semantic caching on LangCache
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- This is a [PyLate](https://github.com/lightonai/pylate) model finetuned from [lightonai/GTE-ModernColBERT-v1](https://huggingface.co/lightonai/GTE-ModernColBERT-v1) on the [LangCache Sentence Pairs (subsets=['all'], train+val=True)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v1) dataset. It maps sentences & paragraphs to sequences of 128-dimensional dense vectors and can be used for semantic textual similarity using the MaxSim operator.
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  ## Model Details
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@@ -33,7 +33,7 @@ This is a [PyLate](https://github.com/lightonai/pylate) model finetuned from [li
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  - **Base model:** [lightonai/GTE-ModernColBERT-v1](https://huggingface.co/lightonai/GTE-ModernColBERT-v1) <!-- at revision 6605e431bed9b582d3eff7699911d2b64e8ccd3f -->
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  - **Document Length:** 512 tokens
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  - **Query Length:** 512 tokens
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- - **Output Dimensionality:** 128 tokens
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  - **Similarity Function:** MaxSim
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  - **Training Dataset:**
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  - [LangCache Sentence Pairs (subsets=['all'], train+val=True)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v1)
@@ -52,6 +52,7 @@ This is a [PyLate](https://github.com/lightonai/pylate) model finetuned from [li
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  ColBERT(
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  (0): Transformer({'max_seq_length': 511, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
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  (1): Dense({'in_features': 768, 'out_features': 128, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity', 'use_residual': False})
 
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  )
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  ```
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  # Redis fine-tuned late-interaction ColBERT model for semantic caching on LangCache
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+ This is a [PyLate](https://github.com/lightonai/pylate) model finetuned from [lightonai/GTE-ModernColBERT-v1](https://huggingface.co/lightonai/GTE-ModernColBERT-v1) on the [LangCache Sentence Pairs (subsets=['all'], train+val=True)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v1) dataset. It maps sentences & paragraphs to sequences of 768-dimensional dense vectors and can be used for semantic textual similarity using the MaxSim operator.
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  ## Model Details
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  - **Base model:** [lightonai/GTE-ModernColBERT-v1](https://huggingface.co/lightonai/GTE-ModernColBERT-v1) <!-- at revision 6605e431bed9b582d3eff7699911d2b64e8ccd3f -->
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  - **Document Length:** 512 tokens
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  - **Query Length:** 512 tokens
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+ - **Output Dimensionality:** 768 tokens
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  - **Similarity Function:** MaxSim
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  - **Training Dataset:**
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  - [LangCache Sentence Pairs (subsets=['all'], train+val=True)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v1)
 
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  ColBERT(
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  (0): Transformer({'max_seq_length': 511, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
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  (1): Dense({'in_features': 768, 'out_features': 128, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity', 'use_residual': False})
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+ (2): Dense({'in_features': 128, 'out_features': 768, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity', 'use_residual': False})
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  )
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  ```
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modules.json CHANGED
@@ -10,5 +10,11 @@
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  "name": "1",
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  "path": "1_Dense",
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  "type": "pylate.models.Dense.Dense"
 
 
 
 
 
 
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  }
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  ]
 
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  "name": "1",
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  "path": "1_Dense",
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  "type": "pylate.models.Dense.Dense"
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+ },
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+ {
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+ "idx": 2,
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+ "name": "2",
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+ "path": "2_Dense",
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+ "type": "pylate.models.Dense.Dense"
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  }
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  ]