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4689b4d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | """Hugging Face configuration for compliantLLM."""
from transformers import PretrainedConfig
class CompliantLLMConfig(PretrainedConfig):
model_type = "compliant_llm"
def __init__(
self,
input_vocab_size=256,
output_vocab_size=3,
max_context=1024,
output_length=3,
d_model=64,
n_heads=4,
n_layers=2,
ffn_dim=128,
dropout=0.0,
output_tokens=None,
**kwargs,
):
super().__init__(**kwargs)
self.input_vocab_size = input_vocab_size
self.output_vocab_size = output_vocab_size
self.max_context = max_context
self.output_length = output_length
self.d_model = d_model
self.n_heads = n_heads
self.n_layers = n_layers
self.ffn_dim = ffn_dim
self.dropout = dropout
self.output_tokens = output_tokens or [
"Sorry, but that question violates GDPR.",
"<|end_turn|>",
"<|eos|>",
]
if self.input_vocab_size != 256:
raise ValueError("compliantLLM requires exactly 256 input tokens")
if self.output_vocab_size != 3 or self.output_length != 3:
raise ValueError("compliantLLM requires exactly three output tokens and positions")
if self.max_context != 1024:
raise ValueError("compliantLLM requires a 1024-token context")
|