Locutusque
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library_name: transformers
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# Model Card for
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<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:**
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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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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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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### Downstream Use [optional]
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<!-- 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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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical 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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## Training Details
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[
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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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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:**
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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[More Information Needed]
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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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[More Information Needed]
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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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- **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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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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library_name: transformers
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license: llama3.1
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datasets:
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- QuasarResearch/apollo-preview-v0.4
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language:
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- en
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pipeline_tag: text-generation
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# Model Card for Locutusque/Apollo-0.4-Llama-3.1-8B
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<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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Fine-tuned Llama-3.1-8B on QuasarResearch/apollo-preview-v0.4. Results in a decent roleplaying language model, that isn't dumb.
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- **Developed by:** Locutusque
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- **Model type:** Llama3.1
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- **Language(s) (NLP):** English
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- **License:** Llama 3.1 Community License Agreement
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Demo:** https://huggingface.co/spaces/Locutusque/Locutusque-Models
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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RP/ERP, instruction following, conversation, etc
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## Bias, Risks, and Limitations
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This model is completely uncensored - use at your own risk.
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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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## Training Details
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[QuasarResearch/apollo-preview-v0.4](https://huggingface.co/datasets/QuasarResearch/apollo-preview-v0.4)
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#### Training Hyperparameters
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- **Training regime:** bf16 non-mixed precision
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## Evaluation
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| Tasks |Version|Filter|n-shot| Metric | | Value | |Stderr|
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|---------------------------------|------:|------|-----:|-----------------|---|-------:|---|-----:|
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|agieval_nous | 0.0|none | |acc_norm |↑ | 0.3833|± |0.0094|
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| - agieval_aqua_rat | 1.0|none | 0|acc |↑ | 0.2598|± |0.0276|
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| | |none | 0|acc_norm |↑ | 0.2323|± |0.0265|
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| - agieval_logiqa_en | 1.0|none | 0|acc |↑ | 0.3825|± |0.0191|
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| | |none | 0|acc_norm |↑ | 0.3856|± |0.0191|
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| - agieval_lsat_ar | 1.0|none | 0|acc |↑ | 0.1913|± |0.0260|
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| | |none | 0|acc_norm |↑ | 0.1826|± |0.0255|
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| - agieval_lsat_lr | 1.0|none | 0|acc |↑ | 0.4216|± |0.0219|
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| | |none | 0|acc_norm |↑ | 0.4216|± |0.0219|
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| - agieval_lsat_rc | 1.0|none | 0|acc |↑ | 0.5613|± |0.0303|
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| | |none | 0|acc_norm |↑ | 0.5056|± |0.0305|
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| - agieval_sat_en | 1.0|none | 0|acc |↑ | 0.6553|± |0.0332|
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| | |none | 0|acc_norm |↑ | 0.6068|± |0.0341|
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| - agieval_sat_en_without_passage| 1.0|none | 0|acc |↑ | 0.3835|± |0.0340|
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| | |none | 0|acc_norm |↑ | 0.3738|± |0.0338|
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| - agieval_sat_math | 1.0|none | 0|acc |↑ | 0.4136|± |0.0333|
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| | |none | 0|acc_norm |↑ | 0.3227|± |0.0316|
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|arc_challenge | 1.0|none | 0|acc |↑ | 0.5179|± |0.0146|
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| | |none | 0|acc_norm |↑ | 0.5580|± |0.0145|
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|eq_bench | 2.1|none | 0|eqbench |↑ | 63.1277|± |2.3905|
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| | |none | 0|percent_parseable|↑ |100.0000|± |0.0000|
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|truthfulqa_mc2 | 2.0|none | 0|acc |↑ | 0.5310|± |0.0150|
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