---
license: apache-2.0
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- sprifi
datasets:
- sprifi/OpenElisaDataset
base_model:
- sprifi/OpenElisa
---

# Model Card for SpriFi's OpenElisa AI Model

<!-- Provide a quick summary of what the model is/does. -->
The OpenElisa is a fine-tuned, open-sourced version of SpriFi's native Elisa AI. Learn more at https://sprifi.com/
## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

- **Developed by:** SpriFi
- **Funded by:** SpriFi
- **Model type:** Fine-tuned open-source
- **Language(s) (NLP):** English
- **License:** Apache 2.0
- **Finetuned from model:** Elisa AI by SpriFi

### Model Sources

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/sprifi
- **Paper:** https://huggingface.co/papers/1910.09700
- **Demo:** https://huggingface.co/spaces/sprifi/Elisa-AI

## Uses

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### Direct Use

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[More Information Needed]

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### 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

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### Results

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#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

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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]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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