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@@ -177,14 +177,21 @@ sparse_rep = expander.expand(
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  ```
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  ## 8. With HuggingFace
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  ```python
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  import torch
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  from transformers import AutoModelForMaskedLM, AutoTokenizer
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  tokenizer = AutoTokenizer.from_pretrained('prithivida/Splade_PP_en_v1')
 
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  model = AutoModelForMaskedLM.from_pretrained('prithivida/Splade_PP_en_v1')
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  model.to(device)
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@@ -216,6 +223,7 @@ for k, v in sorted_d.items():
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  bow_rep.append((reverse_voc[k], round(v,2)))
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  print("SPLADE BOW rep:\n", bow_rep)
 
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  ```
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  ## BEIR Zeroshot ODD performance:
 
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  ```
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+
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  ## 8. With HuggingFace
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+ **NOTEBOOK USERS, please login first**
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+ ```
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+ !huggingface-cli login
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+ ```
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+
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  ```python
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  import torch
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  from transformers import AutoModelForMaskedLM, AutoTokenizer
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  tokenizer = AutoTokenizer.from_pretrained('prithivida/Splade_PP_en_v1')
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+ reverse_voc = {v: k for k, v in tokenizer.vocab.items()}
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  model = AutoModelForMaskedLM.from_pretrained('prithivida/Splade_PP_en_v1')
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  model.to(device)
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  bow_rep.append((reverse_voc[k], round(v,2)))
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  print("SPLADE BOW rep:\n", bow_rep)
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+
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  ```
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  ## BEIR Zeroshot ODD performance: