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tldr_headline_gen
predibase/tldr_headline_gen
tldr_headline_gen is a text generation model from predibase. Use it when you need the model to write or continue text. It is set up for peft.
Description: Headline generation given news content\ Original dataset: https://huggingface.co/datasets/JulesBelveze/tldrnews \ ---\ Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \…
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At a glance
- Task
- Text Generation
- Library
- peft
- Access
- Public
- Created
- Feb 19, 2024
- Updated
- Feb 21, 2024
- SHA
- fb10e14b
Try a prompt
Base models
Model card
From the Hugging Face model README
Description: Headline generation given news content
Original dataset: https://huggingface.co/datasets/JulesBelveze/tldr_news
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land!
The adapter_category is Summarization and the name is News Headline Generation (tldr_news)
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Sample input: The following passage is content from a news report. Please summarize this passage in one sentence or less.\n\nPassage: Jeffrey Berns, CEO of Blockchains LLC, wants the Nevada government to allow companies like his to form local governments on land they own, granting them power over everything from schools to law enforcement. Berns envisions a city based on digital currencies and blockchain storage. His company is proposing to build a 15,000 home town 12 miles east of Reno. Nevada Lawmakers have responded with intrigue and skepticism. The proposed legislation has yet to be formally filed or discussed in public hearings.\n\nSummary:
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Sample output: Blockchain CEO wants to build a city in Nevada
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Try using this adapter yourself!
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "predibase/tldr_headline_gen"
model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)
- Task
- Text Generation
- Library
- peft
- Created
- Feb 19, 2024
- Updated
- Feb 21, 2024