Llama 3 8B Accessibility Audit
Published by @a11y_forge · Community adapter
WCAG 2.1 accessibility audit report generation from HTML snippets. Identifies missing alt text, improper heading hierarchy, low contrast ratios, and missing ARIA roles. Outputs prioritised remediation steps.
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct")
base = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct")
model = PeftModel.from_pretrained(base, "modelforgelab/llama3-8b-accessibility-lora")
inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Compatibility
- transformers>=4.40
- vLLM
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