Text Generation
Transformers
PyTorch
English
olmo2
conversational
Inference Endpoints
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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ language: en
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+ model-index:
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+ - name: allenai/open_instruct_dev
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+ results:
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+ - task:
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+ type: preference_evaluation
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+ dataset:
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+ name: reward-bench
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+ type: allenai/reward-bench
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+ metrics:
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+ - type: accuracy
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+ value: 1.0
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+ - type: accuracy
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+ value: 1.0
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+ - type: accuracy
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+ value: 1.0
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+ - type: accuracy
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+ value: 1.0
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+ ---
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+
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+ # Model Card for allenai/open_instruct_dev
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+ ## Model Details
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+ ### Model Description
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+
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+ ## Uses
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+ ## Bias, Risks, and Limitations
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+ ### Recommendations
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+ ## How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ [More Information Needed]
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+
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+ ## Training Details
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+ ### Training Data
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+ ### Training Procedure
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+ #### Preprocessing [optional]
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+ #### Training Hyperparameters
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+ ## Evaluation
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+ ### Testing Data, Factors & Metrics
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+ #### Factors
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+ [More Information Needed]
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+ #### Metrics
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+ ### Results
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+ #### Summary
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+ ## Model Examination [optional]
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+ <!-- Relevant interpretability work for the model goes here -->
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+ ## Environmental Impact
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+ ## Technical Specifications [optional]
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+ ### Model Architecture and Objective
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+ [More Information Needed]
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+ ### Compute Infrastructure
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+ #### Hardware
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+ ## Glossary [optional]
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+ ## More Information [optional]
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