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@@ -6,17 +6,35 @@ datasets:
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  - allenai/scirepeval
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  ---
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- # Adapter `allenai/specter2_aug2023refresh_classification` for `allenai/specter2_aug2023refresh_base`
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- An [adapter](https://adapterhub.ml) for the `None` model that was trained on the [allenai/scirepeval](https://huggingface.co/datasets/allenai/scirepeval/) dataset.
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- This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
 
 
 
 
 
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  **Dec 2023 Update:**
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  Model usage updated to be compatible with latest versions of transformers and adapters (newly released update to adapter-transformers) libraries.
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  ## Usage
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  First, install `adapters`:
@@ -35,20 +53,6 @@ model = AutoAdapterModel.from_pretrained("allenai/specter2_aug2023refresh_base")
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  adapter_name = model.load_adapter("allenai/specter2_aug2023refresh_classification", source="hf", set_active=True)
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  ```
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- **\*\*\*\*\*\*Update\*\*\*\*\*\***
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-
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- This update introduces a new set of SPECTER 2.0 models with the base transformer encoder pre-trained on an extended citation dataset containing more recent papers.
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- For benchmarking purposes please use the existing SPECTER 2.0 [models](https://huggingface.co/allenai/specter2) w/o the **aug2023refresh** suffix.
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-
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- # SPECTER 2.0 (Base)
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- SPECTER 2.0 is the successor to [SPECTER](https://huggingface.co/allenai/specter) and is capable of generating task specific embeddings for scientific tasks when paired with [adapters](https://huggingface.co/models?search=allenai/specter-2_).
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- This is the base model to be used along with the adapters.
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- Given the combination of title and abstract of a scientific paper or a short texual query, the model can be used to generate effective embeddings to be used in downstream applications.
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-
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- **Note:For general embedding purposes, please use [allenai/specter2](https://huggingface.co/allenai/specter2).**
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-
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- **To get the best performance on a downstream task type please load the associated adapter with the base model as in the example below.**
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-
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  # Model Details
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  ## Model Description
 
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  - allenai/scirepeval
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  ---
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+ ## SPECTER2
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ SPECTER2 is a family of models that succeeds [SPECTER](https://huggingface.co/allenai/specter) and is capable of generating task specific embeddings for scientific tasks when paired with [adapters](https://huggingface.co/models?search=allenai/specter-2_).
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+ Given the combination of title and abstract of a scientific paper or a short texual query, the model can be used to generate effective embeddings to be used in downstream applications.
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+
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+ **Note:For general embedding purposes, please use [allenai/specter2](https://huggingface.co/allenai/specter2).**
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+
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+ **To get the best performance on a downstream task type please load the associated adapter () with the base model as in the example below.**
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  **Dec 2023 Update:**
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  Model usage updated to be compatible with latest versions of transformers and adapters (newly released update to adapter-transformers) libraries.
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+ **\*\*\*\*\*\*Update\*\*\*\*\*\***
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+
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+ This update introduces a new set of SPECTER 2.0 models with the base transformer encoder pre-trained on an extended citation dataset containing more recent papers.
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+ For benchmarking purposes please use the existing SPECTER 2.0 models w/o the **aug2023refresh** suffix viz. [allenai/specter2_base](https://huggingface.co/allenai/specter2_base).
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+
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+
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+ # Adapter `allenai/specter2_aug2023refresh_classification` for `allenai/specter2_aug2023refresh_base`
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+
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+ An [adapter](https://adapterhub.ml) for the `None` model that was trained on the [allenai/scirepeval](https://huggingface.co/datasets/allenai/scirepeval/) dataset.
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+
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+ This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
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+
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+
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  ## Usage
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  First, install `adapters`:
 
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  adapter_name = model.load_adapter("allenai/specter2_aug2023refresh_classification", source="hf", set_active=True)
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  ```
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  # Model Details
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  ## Model Description