
# cicero-gpt2

<!-- Provide a quick summary of what the model is/does. -->

GroNLP/gpt2-small-italian version fine-tuned with italian civil judgments. 

## Model Details

### Model Description

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- **Developed by:** Marco Calamo, Francesca De Luzi, Mattia Macrì, Tommaso Mencattini, Massimo Mecella
- **Model type:** gpt2-small-italian
- **Language(s) (NLP):** italian
- **License:** openrail
- **Finetuned from model:** [GroNLP/gpt-2-small](https://huggingface.co/GroNLP/gpt2-small-italian)
- 
### Model Sources

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

- **Repository:** [Github](https://github.com/MattiaMacri/Cicero)
- **Paper [optional]:** [More Information Needed]

## 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. -->
Used to generate part of sentences based upon user input. All sensible data are hidden by design.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

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[More Information Needed]

### Training Procedure 

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#### Preprocessing [optional]

[More Information Needed]


#### 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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[More Information Needed]

## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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[More Information Needed]

#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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[More Information Needed]

## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->


- **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

[More Information Needed]

### Compute Infrastructure

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#### Hardware

[More Information Needed]

#### Software

[More Information Needed]

## 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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{"language": ["it"], "license": "openrail", "metrics": ["perplexity"]}
transformers pytorch safetensors gpt2 text-generation it license:openrail autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #it #license-openrail #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# cicero-gpt2



GroNLP/gpt2-small-italian version fine-tuned with italian civil judgments. 

## Model Details

### Model Description



- Developed by: Marco Calamo, Francesca De Luzi, Mattia Macrì, Tommaso Mencattini, Massimo Mecella
- Model type: gpt2-small-italian
- Language(s) (NLP): italian
- License: openrail
- Finetuned from model: GroNLP/gpt-2-small
- 
### Model Sources



- Repository: Github
- Paper [optional]: 

## Uses



### Direct Use


Used to generate part of sentences based upon user input. All sensible data are hidden by design.

## How to Get Started with the Model

Use the code below to get started with the model.



## Training Details

### Training Data





### Training Procedure 



#### Preprocessing [optional]




#### Training Hyperparameters

- Training regime:  

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





## Evaluation



### Testing Data, Factors & Metrics

#### Testing Data





#### Factors





#### Metrics





### Results



#### Summary



## Model Examination [optional]





## Environmental Impact




- Hardware Type: 
- Hours used: 
- Cloud Provider: 
- Compute Region: 
- Carbon Emitted: 

## Technical Specifications [optional]

### Model Architecture and Objective



### Compute Infrastructure



#### Hardware



#### Software



[optional]



BibTeX:



APA:



## Glossary [optional]





## More Information [optional]



## Model Card Authors [optional]



## Model Card Contact



# cicero-gpt2



GroNLP/gpt2-small-italian version fine-tuned with italian civil judgments. ## Model Details ### Model Description



- Developed by: Marco Calamo, Francesca De Luzi, Mattia Macrì, Tommaso Mencattini, Massimo Mecella
- Model type: gpt2-small-italian
- Language(s) (NLP): italian
- License: openrail
- Finetuned from model: GroNLP/gpt-2-small
- ### Model Sources



- Repository: Github
- Paper [optional]: ## Uses ### Direct Use


Used to generate part of sentences based upon user input. All sensible data are hidden by design. ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Details ### Training Data ### Training Procedure #### Preprocessing [optional] #### Training Hyperparameters

- Training regime: #### Speeds, Sizes, Times [optional] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data #### Factors #### Metrics ### Results #### Summary ## Model Examination [optional] ## Environmental Impact




- Hardware Type: 
- Hours used: 
- Cloud Provider: 
- Compute Region: 
- Carbon Emitted: ## Technical Specifications [optional] ### Model Architecture and Objective ### Compute Infrastructure #### Hardware #### Software



[optional]



BibTeX:



APA: ## Glossary [optional] ## More Information [optional] ## Model Card Authors [optional] ## Model Card Contact
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #it #license-openrail #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # cicero-gpt2



GroNLP/gpt2-small-italian version fine-tuned with italian civil judgments. ## Model Details ### Model Description



- Developed by: Marco Calamo, Francesca De Luzi, Mattia Macrì, Tommaso Mencattini, Massimo Mecella
- Model type: gpt2-small-italian
- Language(s) (NLP): italian
- License: openrail
- Finetuned from model: GroNLP/gpt-2-small
- ### Model Sources



- Repository: Github
- Paper [optional]: ## Uses ### Direct Use


Used to generate part of sentences based upon user input. All sensible data are hidden by design. ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Details ### Training Data ### Training Procedure #### Preprocessing [optional] #### Training Hyperparameters

- Training regime: #### Speeds, Sizes, Times [optional] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data #### Factors #### Metrics ### Results #### Summary ## Model Examination [optional] ## Environmental Impact




- Hardware Type: 
- Hours used: 
- Cloud Provider: 
- Compute Region: 
- Carbon Emitted: ## Technical Specifications [optional] ### Model Architecture and Objective ### Compute Infrastructure #### Hardware #### Software



[optional]



BibTeX:



APA: ## Glossary [optional] ## More Information [optional] ## Model Card Authors [optional] ## Model Card Contact