---
language:
- en
library_name: transformers
license: other
---

# Model Card for ContractAssist model

<!-- Provide a quick summary of what the model is/does. [Optional] -->
Intruction tuned model using FlanT5-XXL on data generated via ChatGPT for generating and/or modifying the Legal Clauses.



# Model Details

## Model Description

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

- **Developed by:** Jaykumar Kasundra, Shreyans Dhankhar
- **Model type:** Language model
- **Language(s) (NLP):** en
- **License:** other
- **Resources for more information:** 

    - [Associated Paper](<Add Link>)

# Uses


</details>

### Running the model on a GPU using different precisions

#### FP16

<details>
<summary> Click to expand </summary>

```python
# pip install accelerate peft bitsandbytes
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
from peft import PeftModel,PeftConfig 
tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xxl")
model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xxl", device_map="auto", torch_dtype=torch.float16)
input_text = "translate English to German: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))
```

</details>

#### INT8

<details>
<summary> Click to expand </summary>

```python
# pip install bitsandbytes accelerate
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xxl")
model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xxl", device_map="auto", load_in_8bit=True)
input_text = "translate English to German: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))
```

</details>

<!-- 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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The model can directly be used to generate/modify legal clauses and help assist in drafting contracts. It likely works best on english language.

## Compute Infrastructure

Amazon SageMaker Training Job.

### Hardware

1 x 24GB NVIDIA A10G

### Software

Transformers, PEFT, BitsandBytes

# Citation

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

**BibTeX:**

<Coming Soon>

# Model Card Authors

<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->

Jaykumar Kasundra, Shreyans Dhankhar