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liar_stabilityai_stablelm-2-zephyr-1_6b_PROMPT_TUNING_CAUSAL_LM

Text Classification
Transformers
Safetensors
English
Inference Endpoints
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metadata
library_name: transformers
language:
  - en
metrics:
  - accuracy: 62.3 % accuracy on the 2-label liar test set.
pipeline_tag: text-classification

Model Card for Model ID

This model classifies news statements as true or false.

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

How to Get Started with the Model

Use the code below to get started with the model.

from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model = AutoPeftModelForCausalLM.from_pretrained("baris-yazici/liar_stabilityai_stablelm-2-zephyr-1_6b_PROMPT_TUNING_CAUSAL_LM").to("cuda")
tokenizer = AutoTokenizer.from_pretrained("stabilityai/stablelm-2-zephyr-1_6b")

Training Details

Training Data

The liar dataset can be accessed from: https://huggingface.co/datasets/liar.

Training Procedure

Prompt tuning was used: https://huggingface.co/docs/peft/task_guides/prompt_based_methods). Trained on 2 epochs due to computational limitations.