---
license: mit
datasets:
- ACE05
- bc5cdr
- conll2003
- ncbi_disease
- conll2012_ontonotesv5
- rams
- tacred
- wnut_17
- broad_twitter_corpus
- casie
- CrossNER
- e3c
- fabner
- harvey_ner
- mit_movies
- mit_restaurant
- multinerd
- WikiEvent
language:
- en
metrics:
- f1
pipeline_tag: text-generation
---
# Model Card for Model ID

GoLLIE **G**uideline-f**o**llowing **L**arge **L**anguage Model for **IE**, is a model able to improve zero-shot results on unseen IE tasks by virtue of being fine-tuned to comply with  annotation guidelines.

## Model Details

```Python

# The following lines describe the task definition
@dataclass
class PersonTemplate(Template):
  """Person templates encodes the information about the given query
  Person entity."""
  query: str # The Person entity query
  alternate_names: Optional[List[Name]] = None
  """Names used to refer to the query person that are distinct from the
  'official' name. Including: aliases, stage names, abbreviations ..."""
  date_of_birth: Optional[Value] = None
  """The date on which the query person was born."""
  age: Optional[Value] = None
  """A reported age of the query person."""
  city_of_birth: Optional[Name] = None
  """The geopolitical entity at the municipality level (city, town, or
  village) in which the query person was born"""
  date_of_death: Optional[Value] = None
  """The date of the query person's death."""

# This is the text to analyze
text = "Mongolian Prime Minister M. Enkhbold arrived on Monday. "
# The annotation instances that take place in the text above are listed here
result = [
  PersonTemplate(
    query="M. Enkhbold",
    countries_of_residence=[Name("Mongolian")],
    title=[String("Prime Minister")],
  ),
]

```


### Model Description

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



- **Developed by:** Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, Eneko Agirre
- **Institution:** HiTZ Basque Center for Language Technology - Ixa, University of the Basque Country UPV/EHU
- **Model type:** CODE-LLaMA2
- **Language(s) (NLP):** English
- **License:** LLaMA2 License for the base and merged model. Apache 2.0 for pre-trained LoRA Adapters
- **Finetuned from model [optional]:** CODE-LLaMA2

### Model Sources [optional]

- **Repository:** https://github.com/osainz59/CoLLIE
- **Paper [optional]:** **Coming soon**
- **Demo [optional]:** **Coming soon**

## 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. -->

[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.

[More Information Needed]

## Training Details

### Training Data

<!-- This should link to a Data 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. -->

[More Information Needed]

### Training Procedure 

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### 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]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

<!-- This should link to a Data Card if possible. -->

[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

[More Information Needed]

#### Summary



## Model Examination [optional]

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

[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 -->

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

[More Information Needed]

### Compute Infrastructure

[More Information Needed]

#### Hardware

[More Information Needed]

#### Software

[More Information Needed]

## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Model Card Authors [optional]

[More Information Needed]

## Model Card Contact

[More Information Needed]