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Jasper Kyle Catapang
2023-06-01 12:44:54 +00:00
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--- ---
license: apache-2.0 license: cc-by-sa-4.0
pipeline_tag: text-generation pipeline_tag: text-generation
--- ---
@@ -24,9 +24,13 @@ FinOPT-Washington is designed to assist users in obtaining relevant and reliable
The model is intended to be used by individuals seeking information about financial topics, as well as developers and researchers working on natural language processing (NLP) tasks in the financial domain. The model is intended to be used by individuals seeking information about financial topics, as well as developers and researchers working on natural language processing (NLP) tasks in the financial domain.
## Usage ## Usage
To use FinOPT-Washington, you may use the following template: To use FinOPT-Washington, you are required to provide attribution in accordance with the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. Please include the following attribution notice when utilizing FinOPT-Washington in your work:
```python ```python
# This code uses FinOPT-Washington, a language model developed by MayaPH.
# The model is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
# For more information, visit: https://creativecommons.org/licenses/by-sa/4.0/
from transformers import AutoTokenizer, AutoModelForCausalLM from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MayaPH/FinOPT-Washington") tokenizer = AutoTokenizer.from_pretrained("MayaPH/FinOPT-Washington")
@@ -34,6 +38,8 @@ tokenizer = AutoTokenizer.from_pretrained("MayaPH/FinOPT-Washington")
model = AutoModelForCausalLM.from_pretrained("MayaPH/FinOPT-Washington") model = AutoModelForCausalLM.from_pretrained("MayaPH/FinOPT-Washington")
``` ```
Please ensure that you include the relevant attribution notice in your code or any other form of usage to comply with the license terms.
## Limitations and Caveats ## Limitations and Caveats
While FinOPT-Washington has been fine-tuned on a financial question-answering dataset, it is important to note the following limitations and caveats: While FinOPT-Washington has been fine-tuned on a financial question-answering dataset, it is important to note the following limitations and caveats: