PerplexityViewer / config.py
Bram van Es
added models
797ad44
# Configuration file for PerplexityViewer
# Default models for different types
DEFAULT_MODELS = {
"decoder": [
"gpt2",
"distilgpt2",
"microsoft/DialoGPT-small",
"microsoft/DialoGPT-medium",
"openai-gpt"
],
"encoder": [
"bert-base-uncased",
"bert-base-cased",
"distilbert-base-uncased",
"roberta-base",
"albert-base-v2"
"UMCU/CardioMedRoBERTa.nl",
"UMCU/CardioBERTa_base.nl",
"UMCU/CardioBERTa.nl_clinical",
"UMCU/CardioDeBERTa.nl",
"UMCU/CardioDeBERTa.nl_clinical",
"CLTL/MedRoBERTa.nl",
"DTAI-KULeuven/robbert-2023-dutch-base",
"DTAI-KULeuven/robbert-2023-dutch-large"
]
}
# Model display settings
MODEL_SETTINGS = {
"max_length": 512,
"torch_dtype": "float16",
"device_map": "auto"
}
# Visualization settings
VIZ_SETTINGS = {
"max_perplexity_display": 50.0, # Cap visualization at this perplexity value
"color_scheme": {
"low_perplexity": {"r": 46, "g": 204, "b": 113}, # Green for low perplexity (confident)
"medium_perplexity": {"r": 241, "g": 196, "b": 15}, # Yellow for medium perplexity
"high_perplexity": {"r": 231, "g": 76, "b": 60}, # Red for high perplexity (uncertain)
"background_alpha": 0.7, # Background transparency
"border_alpha": 0.9 # Border transparency
},
"thresholds": {
"low_threshold": 0.3, # Below this is low perplexity (green)
"high_threshold": 0.7 # Above this is high perplexity (red)
},
"displacy_options": {
"ents": ["PP"],
"colors": {}
}
}
# Processing settings
PROCESSING_SETTINGS = {
"epsilon": 1e-10 # Small value to avoid log(0)
}
# UI settings
UI_SETTINGS = {
"theme": "soft",
"title": "πŸ“ˆ Perplexity Viewer",
"description": """
Visualize per-token perplexity using color gradients.
- **Red**: High perplexity (model is uncertain)
- **Green**: Low perplexity (model is confident)
Choose between decoder models (like GPT) for true perplexity or encoder models (like BERT) for pseudo-perplexity via MLM.
""",
"examples": [
{
"text": "The quick brown fox jumps over the lazy dog.",
"model": "gpt2",
"type": "decoder"
},
{
"text": "The capital of France is Paris.",
"model": "bert-base-uncased",
"type": "encoder"
},
{
"text": "Quantum entanglement defies classical physics intuition completely.",
"model": "distilgpt2",
"type": "decoder"
},
{
"text": "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo.",
"model": "gpt2",
"type": "decoder"
},
{
"text": "Machine learning algorithms require computational resources.",
"model": "distilbert-base-uncased",
"type": "encoder"
}
]
}
# Error messages
ERROR_MESSAGES = {
"empty_text": "Please enter some text to analyze.",
"model_load_error": "Error loading model {model_name}: {error}",
"processing_error": "Error processing text: {error}",
"no_tokens_masked": "No tokens were masked during MLM processing.",
"invalid_model_type": "Invalid model type. Must be 'encoder' or 'decoder'."
}