File size: 2,679 Bytes
d340bf5 | 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 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | from __future__ import annotations
from typing import Any, Dict, Optional
from transformers import AutoConfig, PretrainedConfig
class OpenThaiSystemOneConfig(PretrainedConfig):
"""Config = a text-tower config (Qwen3.5 text) + slot-head settings [+ vision tower + point head for the -Vision variant].
vision_config is None for the text-only line (v0.x): the model then wraps `Qwen3_5TextModel` and its state-dict
layout is unchanged. With a vision_config the model wraps the multimodal `Qwen3_5Model` (visual + language_model)
and gains a PointHead for `point` questions.
"""
model_type = "openthai_systemone"
sub_configs = {"text_config": AutoConfig, "vision_config": AutoConfig}
def __init__(
self,
text_config: Optional[Dict[str, Any] | PretrainedConfig] = None,
n_slots: int = 256,
abstain_slot: int = 255,
answer_token_id: Optional[int] = None,
head_bias: bool = True,
n_temperatures: int = 3, # per question type: choice / score / noul (/ point)
vision_config: Optional[Dict[str, Any] | PretrainedConfig] = None,
image_token_id: Optional[int] = None,
vision_start_token_id: Optional[int] = None,
vision_end_token_id: Optional[int] = None,
point_token_id: Optional[int] = None,
point_head: Optional[Dict[str, Any]] = None, # {"dim": 256, "n_sa_layers": 1, "n_heads": 8}
**kwargs,
):
if isinstance(text_config, dict):
text_config = AutoConfig.for_model(**text_config) if "model_type" in text_config else AutoConfig.for_model("qwen3_5_text", **text_config)
if isinstance(vision_config, dict):
vc = dict(vision_config)
vision_config = AutoConfig.for_model(**vc) if "model_type" in vc else AutoConfig.for_model("qwen3_5_vision", **vc)
self.text_config = text_config
self.vision_config = vision_config
self.n_slots = n_slots
self.abstain_slot = abstain_slot
self.answer_token_id = answer_token_id
self.head_bias = head_bias
self.n_temperatures = n_temperatures
self.image_token_id = image_token_id
self.vision_start_token_id = vision_start_token_id
self.vision_end_token_id = vision_end_token_id
self.point_token_id = point_token_id
self.point_head = point_head
super().__init__(**kwargs)
@property
def is_vision(self) -> bool:
return self.vision_config is not None
@property
def hidden_size(self) -> int:
return self.text_config.hidden_size
@property
def vocab_size(self) -> int:
return self.text_config.vocab_size
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