webnizam/gemma-unintended-consequences-2b

Model Card for Gemma 2b - Unintended Consequences

This model is a Gemma-based model fine-tuned for generating text related to the unintended consequences of various actions or decisions.

Model Details

Model Description

This is a Gemma model fine-tuned for the task of generating text about unintended consequences. The model has been trained on a dataset of text examples that describe various actions and their unintended consequences.

• Developed by: Falcons.AI
• Model type: GemmaForCausalLM
• Language(s) (NLP): English
• Finetuned from model: gemma-2b-it

Model Sources

• Repository: webnizam/gemma-unintended-consequences-2b

Uses

Direct Use

This model can be used directly to generate text about unintended consequences of various actions or decisions. It can be useful for brainstorming, risk assessment, or educational purposes.

How to Get Started with the Model

Use the following code to get started with the model:

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("webnizam/gemma-unintended-consequences-2b")
model = AutoModelForCausalLM.from_pretrained("webnizam/gemma-unintended-consequences-2b")

text = "<start_of_text> Outsourcing Manufacturing to Low-Cost Countries"
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))