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@@ -40,7 +40,7 @@ It achieves the following results on the evaluation set:
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  ## Model details
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- - **Fine-tuned by:** Laiyer.ai
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  - **Model type:** distilroberta-base
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  - **Language(s) (NLP):** English
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  - **License:** Apache license 2.0
@@ -62,8 +62,8 @@ Additionally, `distilroberta-base` is case-sensitive model.
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  import torch
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- tokenizer = AutoTokenizer.from_pretrained("laiyer/distilroberta-base-rejection-v1")
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- model = AutoModelForSequenceClassification.from_pretrained("laiyer/distilroberta-base-rejection-v1")
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  classifier = pipeline(
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  "text-classification",
@@ -85,8 +85,8 @@ Loading the model requires the [🤗 Optimum](https://huggingface.co/docs/optimu
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  from optimum.onnxruntime import ORTModelForSequenceClassification
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  from transformers import AutoTokenizer, pipeline
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- tokenizer = AutoTokenizer.from_pretrained("laiyer/distilroberta-base-rejection-v1", subfolder="onnx")
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- model = ORTModelForSequenceClassification.from_pretrained("laiyer/distilroberta-base-rejection-v1", export=False, subfolder="onnx")
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  classifier = pipeline(
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  task="text-classification",
@@ -152,10 +152,10 @@ get help for package usage or contributions, or engage in discussions about LLM
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  ```
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  @misc{distilroberta-base-rejection-v1,
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- author = {Laiyer.ai},
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  title = {Fine-Tuned DistilRoberta-Base for Rejection in the output Detection},
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  year = {2024},
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  publisher = {HuggingFace},
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- url = {https://huggingface.co/laiyer/distilroberta-base-rejection-v1},
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  }
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  ```
 
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  ## Model details
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+ - **Fine-tuned by:** ProtectAI.com
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  - **Model type:** distilroberta-base
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  - **Language(s) (NLP):** English
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  - **License:** Apache license 2.0
 
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  import torch
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+ tokenizer = AutoTokenizer.from_pretrained("ProtectAI/distilroberta-base-rejection-v1")
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+ model = AutoModelForSequenceClassification.from_pretrained("ProtectAI/distilroberta-base-rejection-v1")
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  classifier = pipeline(
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  "text-classification",
 
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  from optimum.onnxruntime import ORTModelForSequenceClassification
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  from transformers import AutoTokenizer, pipeline
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+ tokenizer = AutoTokenizer.from_pretrained("ProtectAI/distilroberta-base-rejection-v1", subfolder="onnx")
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+ model = ORTModelForSequenceClassification.from_pretrained("ProtectAI/distilroberta-base-rejection-v1", export=False, subfolder="onnx")
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  classifier = pipeline(
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  task="text-classification",
 
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  ```
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  @misc{distilroberta-base-rejection-v1,
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+ author = {ProtectAI.com},
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  title = {Fine-Tuned DistilRoberta-Base for Rejection in the output Detection},
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  year = {2024},
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  publisher = {HuggingFace},
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+ url = {https://huggingface.co/ProtectAI/distilroberta-base-rejection-v1},
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  }
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  ```