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TouchGrass configuration for HuggingFace.
Integrates with transformers library.
"""
from typing import Optional, List, Dict, Any
from transformers import PretrainedConfig
class TouchGrassConfig(PretrainedConfig):
"""
Configuration class for TouchGrass model.
Compatible with HuggingFace transformers.
"""
model_type = "touchgrass"
tie_word_embeddings = True
def __init__(
self,
base_model: str = "Qwen/Qwen3.5-3B-Instruct",
model_type: str = "touchgrass",
d_model: int = 2048,
num_layers: int = 36,
num_heads: int = 16,
head_dim: int = 128,
ffn_expansion: float = 2.67,
vocab_size: int = 32000,
max_seq_len: int = 4096,
# Music modules
enable_tab_chord_module: bool = True,
enable_music_theory_module: bool = True,
enable_ear_training_module: bool = True,
enable_eq_adapter: bool = True,
enable_songwriting_module: bool = True,
eq_hidden_dim: int = 32,
eq_loss_weight: float = 0.1,
# Special tokens
special_tokens: Optional[Dict[str, int]] = None,
music_domains: Optional[List[str]] = None,
skill_levels: Optional[List[str]] = None,
notation_tags: Optional[List[str]] = None,
initializer_range: float = 0.02,
**kwargs
):
super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)
self.base_model = base_model
self.model_type = model_type
self.d_model = d_model
self.num_layers = num_layers
self.num_heads = num_heads
self.head_dim = head_dim
self.ffn_expansion = ffn_expansion
self.vocab_size = vocab_size
self.max_seq_len = max_seq_len
self.enable_tab_chord_module = enable_tab_chord_module
self.enable_music_theory_module = enable_music_theory_module
self.enable_ear_training_module = enable_ear_training_module
self.enable_eq_adapter = enable_eq_adapter
self.enable_songwriting_module = enable_songwriting_module
self.eq_hidden_dim = eq_hidden_dim
self.eq_loss_weight = eq_loss_weight
self.special_tokens = special_tokens or {}
self.music_domains = music_domains or ["[GUITAR]", "[PIANO]", "[DRUMS]", "[VOCALS]", "[THEORY]", "[DJ]"]
self.skill_levels = skill_levels or ["[BEGINNER]", "[INTERMEDIATE]", "[ADVANCED]"]
self.notation_tags = notation_tags or ["[TAB]", "[CHORD]", "[SHEET]", "[LYRICS]", "[PROGRESSION]"]
self.initializer_range = initializer_range
@classmethod
def from_pretrained(cls, pretrained_model_name_or_path: str, **kwargs):
"""Load config from pretrained model."""
import json
import os
config_path = os.path.join(pretrained_model_name_or_path, "config.json")
if os.path.exists(config_path):
with open(config_path, "r") as f:
config_dict = json.load(f)
config_dict.update(kwargs)
return cls(**config_dict)
else:
# Return default config
return cls(**kwargs)
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary."""
return {
"model_type": self.model_type,
"base_model": self.base_model,
"d_model": self.d_model,
"num_layers": self.num_layers,
"num_heads": self.num_heads,
"head_dim": self.head_dim,
"ffn_expansion": self.ffn_expansion,
"vocab_size": self.vocab_size,
"max_seq_len": self.max_seq_len,
"enable_tab_chord_module": self.enable_tab_chord_module,
"enable_music_theory_module": self.enable_music_theory_module,
"enable_ear_training_module": self.enable_ear_training_module,
"enable_eq_adapter": self.enable_eq_adapter,
"enable_songwriting_module": self.enable_songwriting_module,
"eq_hidden_dim": self.eq_hidden_dim,
"eq_loss_weight": self.eq_loss_weight,
"special_tokens": self.special_tokens,
"music_domains": self.music_domains,
"skill_levels": self.skill_levels,
"notation_tags": self.notation_tags,
"initializer_range": self.initializer_range,
} |