Text Generation
Transformers
Safetensors
PyTorch
English
gpt_neox
causal-lm
pythia
safety
unlearning
data-filtering
interpretability
pretraining
eleutherai
gpt-neox
wmdp
cbrn
tamper-resistance
research
model-suite
6.9b
circuit-breaking
knowledge-filtering
open-weight
biothreat
safety-research
model-diffing
training-dynamics
text-generation-inference
| library_name: transformers | |
| tags: [] | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| ## Model Details | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. | |
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| ## Uses | |
| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> | |
| ### Direct Use | |
| <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> | |
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| ### Downstream Use [optional] | |
| <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> | |
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| ### Out-of-Scope Use | |
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| ## Bias, Risks, and Limitations | |
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| ### Recommendations | |
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| ## How to Get Started with the Model | |
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| ## Training Details | |
| ### Training Data | |
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| ### Training Procedure | |
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| #### Training Hyperparameters | |
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| ## Evaluation | |
| <!-- This section describes the evaluation protocols and provides the results. --> | |
| ### Testing Data, Factors & Metrics | |
| #### Testing Data | |
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| #### Factors | |
| <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> | |
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| #### Metrics | |
| <!-- These are the evaluation metrics being used, ideally with a description of why. --> | |
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| ### Results | |
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| #### Summary | |
| ## Model Examination [optional] | |
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| ## Environmental Impact | |
| <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> | |
| 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). | |
| - **Hardware Type:** [More Information Needed] | |
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| ## Technical Specifications [optional] | |
| ### Model Architecture and Objective | |
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| ### Compute Infrastructure | |
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| #### Hardware | |
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| ## Citation [optional] | |
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| ## Glossary [optional] | |
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| ## Model Card Authors [optional] | |
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