---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
pipeline_tag: text-generation
---
Description: Content generation given a headline\
Original dataset: https://huggingface.co/datasets/JulesBelveze/tldr_news \
---\
Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
The adapter_category is Other and the name is News Content Generation (tldr_news)\
---\
Sample input: The following headline is the headline of a news report. Please write the content of the news passage based on only this headline.\n\nHeadline: Latest success from Google’s AI group: Controlling a fusion reactor \n\nContent: \
---\
Sample output: Google's AI group has developed a system that can control a fusion reactor. The system uses a deep reinforcement learning algorithm to control the reactor's magnetic field. It can control the reactor's magnetic field with a precision of 0.001%. The system can also learn to control the reactor's plasma. A video is available that shows the system controlling the reactor.\
---\
Try using this adapter yourself!
```
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "predibase/tldr_content_gen"

model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)
```