Files
koboldcpp/conversion/__init__.py
T
Gabe Goodhart 7221e24f57 model : GraniteSWAForCausalLM / GraniteMoeSWAForCausalLM (#25505)
* feat(convert): Add conversion for GraniteSWAForCausalLM

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob, OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(llama): Add granite_swa support

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob, OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(conversion): Add conversion infra for rope_pattern array

NOTE: There is other work also targeting this, so this may be
removed depending on merge order.

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(conversion): Fix SWA pattern logic and support for non-rope layers

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(conversion): Add support for GraniteMoeSWA

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add llama_hparams::has_rope and arch constants

NOTE: This shadows the work done for Granite Speech
https://github.com/ggml-org/llama.cpp/pull/25107

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Add support for per-layer rope determination

Branch: GraniteSWAForCausalLM
AI-usage: full (Bob)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Fix failing flake8 for extra newlines

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* test: Write out SLIDING_WINDOW_PATTERN in llama-model-saver

Branch: GraniteSWAForCausalLM
AI-usage: full (OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert): Fix missing registration for GraniteMoeSWAForCausalLM

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Load MoE params as optional

Branch: GraniteSWAForCausalLM
AI-usage: draft (OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Handle MoE params in conversion

branch: GraniteSWAForCausalLM
AI-usage: full (OpenCode + Qwen3.6-35b)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: Remove unnecessary newline

AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove unnecessary tensor additions to GRANITE architecture

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Correctly handle naming for ffn gate inp

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Always default hparams.rope_pattern to 1s

This isn't strictly necessary, but it will allow other models to rely on
hparams.has_rope(il) without needting to prepopulate.

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Move to has_rope for all granite model architectures

Now that we have a proper hparam for this, it's better to use it and not
require a hacky fallback in the hparam method itself.

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: No hacky rope_finetuned fallback in has_rope

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fully remove rope hparam filling in granitemoe

There are no granitemoe models that use NoPE (it's not actually used in the
layer building below), so this was just dead code.

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Save out rope_pattern in model-saver

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Set hparams.rope_finetuned for round trip

Since the value is _read_ from rope_finetuned, we need to persist it when
the model is saved with the saver.

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Code review cleanup

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

* refactor: Keep gate/up fused for MoE path

Branch: GraniteSWAForCausalLM
AI-usage: full (Claude + Sonnet 5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Skip GRANITE_SWA in model saver

https://github.com/ggml-org/llama.cpp/pull/25505#discussion_r3773175651

Keeping is_swa_impl in the saver can break other models.

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* add sliding window pattern for model in test

* style: Fix indentation

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Fix \r\n

Thanks Claude!

Branch: GraniteSWAForCausalLM
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat: Keep shared expert fused

Branch: GraniteSWAForCausalLM
AI-usage: full (Claude + Sonnet 5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* style: More indentation fixes

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
2026-08-19 16:53:31 +02:00

388 lines
15 KiB
Python

from __future__ import annotations
from .base import (
ModelBase, TextModel, MmprojModel, ModelType, SentencePieceTokenTypes,
logger, _mistral_common_installed, _mistral_import_error_msg,
get_model_architecture, LazyTorchTensor,
)
from typing import Type
__all__ = [
"ModelBase", "TextModel", "MmprojModel", "ModelType", "SentencePieceTokenTypes",
"get_model_architecture", "LazyTorchTensor", "logger",
"_mistral_common_installed", "_mistral_import_error_msg",
"get_model_class", "print_registered_models", "load_all_models",
]
TEXT_MODEL_MAP: dict[str, str] = {
"AfmoeForCausalLM": "afmoe",
"LagunaForCausalLM": "laguna",
"ApertusForCausalLM": "llama",
"ArceeForCausalLM": "llama",
"ArcticForCausalLM": "arctic",
"AudioFlamingo3ForConditionalGeneration": "qwen",
"BaiChuanForCausalLM": "baichuan",
"BaichuanForCausalLM": "baichuan",
"BailingMoeForCausalLM": "bailingmoe",
"BailingMoeV2ForCausalLM": "bailingmoe",
"BailingMoeV3ForCausalLM": "bailingmoe3",
"BambaForCausalLM": "granite",
"BertForMaskedLM": "bert",
"BertForSequenceClassification": "bert",
"BertModel": "bert",
"BitnetForCausalLM": "bitnet",
"BitNetForCausalLM": "bitnet",
"BloomForCausalLM": "bloom",
"BloomModel": "bloom",
"CamembertModel": "bert",
"ChameleonForCausalLM": "chameleon",
"ChameleonForConditionalGeneration": "chameleon",
"ChatGLMForConditionalGeneration": "chatglm",
"ChatGLMModel": "chatglm",
"CodeShellForCausalLM": "codeshell",
"CogVLMForCausalLM": "cogvlm",
"Cohere2MoeForCausalLM": "command_r",
"Cohere2ForCausalLM": "command_r",
"CohereForCausalLM": "command_r",
"DbrxForCausalLM": "dbrx",
"DeciLMForCausalLM": "deci",
"DeepseekForCausalLM": "deepseek",
"DeepseekOCRForCausalLM": "deepseek",
"DeepseekV2ForCausalLM": "deepseek",
"DeepseekV3ForCausalLM": "deepseek",
"DeepseekV32ForCausalLM": "deepseek",
"DFlashDraftModel": "qwen",
"Qwen3DSparkModel": "qwen",
"DSparkDraftModel": "qwen",
"DSparkSpeculator": "qwen",
"DeepseekV4ForCausalLM": "deepseek",
"DeepseekV4DSparkModel": "deepseek",
"DistilBertForMaskedLM": "bert",
"DistilBertForSequenceClassification": "bert",
"DistilBertModel": "bert",
"Dots1ForCausalLM": "dots1",
"DotsOCRForCausalLM": "qwen",
"DreamModel": "dream",
"Ernie4_5ForCausalLM": "ernie",
"Ernie4_5_ForCausalLM": "ernie",
"Ernie4_5_MoeForCausalLM": "ernie",
"EuroBertModel": "bert",
"Exaone4_5_ForConditionalGeneration": "exaone",
"Exaone4ForCausalLM": "exaone",
"ExaoneForCausalLM": "exaone",
"ExaoneMoEForCausalLM": "exaone",
"ExaoneMoeForCausalLM": "exaone",
"FalconForCausalLM": "falcon",
"FalconH1ForCausalLM": "falcon_h1",
"FalconMambaForCausalLM": "mamba",
"GPT2LMHeadModel": "gpt2",
"GPTBigCodeForCausalLM": "starcoder",
"GPTNeoXForCausalLM": "gptneox",
"GPTRefactForCausalLM": "refact",
"Gemma2ForCausalLM": "gemma",
"Gemma3ForCausalLM": "gemma",
"Gemma3ForConditionalGeneration": "gemma",
"Gemma3TextModel": "gemma",
"Gemma3nForCausalLM": "gemma",
"Gemma3nForConditionalGeneration": "gemma",
"Gemma4AssistantForCausalLM": "gemma",
"Gemma4ForConditionalGeneration": "gemma",
"Gemma4ForCausalLM": "gemma",
"Gemma4UnifiedForConditionalGeneration": "gemma",
"Gemma4UnifiedAssistantForCausalLM": "gemma",
"GemmaForCausalLM": "gemma",
"Glm4ForCausalLM": "glm",
"Glm4MoeForCausalLM": "glm",
"Glm4MoeLiteForCausalLM": "glm",
"Glm4vForConditionalGeneration": "glm",
"Glm4vMoeForConditionalGeneration": "glm",
"GlmForCausalLM": "chatglm",
"GlmMoeDsaForCausalLM": "glm",
"GlmOcrForConditionalGeneration": "glm",
"GptOssForCausalLM": "gpt_oss",
"GraniteForCausalLM": "granite",
"GraniteMoeForCausalLM": "granite",
"GraniteMoeHybridForCausalLM": "granite",
"GraniteMoeSharedForCausalLM": "granite",
"GraniteSwitchForCausalLM": "granite",
"GraniteSpeechForConditionalGeneration": "granite",
"GraniteSpeechPlusForConditionalGeneration": "granite",
"GraniteSWAForCausalLM": "granite",
"GraniteMoeSWAForCausalLM": "granite",
"Grok1ForCausalLM": "grok",
"GrokForCausalLM": "grok",
"GroveMoeForCausalLM": "grovemoe",
"HunYuanDenseV1ForCausalLM": "hunyuan",
"HunYuanMoEV1ForCausalLM": "hunyuan",
"HunYuanVLForConditionalGeneration": "hunyuan",
"HYV3ForCausalLM": "hunyuan",
"IQuestCoderForCausalLM": "llama",
"InternLM2ForCausalLM": "internlm",
"InternLM3ForCausalLM": "internlm",
"JAISLMHeadModel": "jais",
"Jais2ForCausalLM": "jais",
"JambaForCausalLM": "jamba",
"JanusForConditionalGeneration": "januspro",
"JinaBertForMaskedLM": "bert",
"JinaBertModel": "bert",
"JinaEmbeddingsV5Model": "bert",
"KORMoForCausalLM": "qwen",
"KimiK25ForConditionalGeneration": "deepseek",
"KimiK3ForConditionalGeneration": "kimi_k3",
"KimiLinearForCausalLM": "kimi_linear",
"KimiLinearModel": "kimi_linear",
"KimiVLForConditionalGeneration": "deepseek",
"LFM2ForCausalLM": "lfm2",
"LLaDAMoEModel": "llada",
"LLaDAMoEModelLM": "llada",
"LLaDAModelLM": "llada",
"LLaMAForCausalLM": "llama",
"Lfm25AudioTokenizer": "lfm2",
"Lfm2BidirectionalModel": "lfm2",
"Lfm2ForCausalLM": "lfm2",
"Lfm2Model": "lfm2",
"Lfm2MoeForCausalLM": "lfm2",
"Llama4ForCausalLM": "llama",
"Llama4ForConditionalGeneration": "llama",
"LlamaBidirectionalModel": "llama",
"LlamaForCausalLM": "llama",
"LlamaModel": "llama",
"Eagle3DraftModel": "llama",
"Eagle3Speculator": "llama",
"Eagle3LlamaForCausalLM": "llama",
"LlamaForCausalLMEagle3": "llama",
"LlavaForConditionalGeneration": "llama",
"LlavaStableLMEpochForCausalLM": "stablelm",
"MPTForCausalLM": "mpt",
"MT5ForConditionalGeneration": "t5",
"MaincoderForCausalLM": "maincoder",
"Mamba2ForCausalLM": "mamba",
"MambaForCausalLM": "mamba",
"MambaLMHeadModel": "mamba",
"MellumForCausalLM": "mellum",
"MiMoV2FlashForCausalLM": "mimo",
"MiMoV2ForCausalLM": "mimo",
"MiniCPM3ForCausalLM": "minicpm",
"MiniCPMForCausalLM": "minicpm",
"MiniCPMV4_6ForConditionalGeneration": "minicpm",
"MiniMaxText01ForCausalLM": "minimax",
"MiniMaxM1ForCausalLM": "minimax",
"MiniMaxM2ForCausalLM": "minimax",
"MiniMaxM3SparseForCausalLM": "minimax",
"MiniMaxM3SparseForConditionalGeneration": "minimax",
"Ministral3ForCausalLM": "mistral3",
"Mistral3ForConditionalGeneration": "mistral3",
"MistralForCausalLM": "llama",
"MixtralForCausalLM": "llama",
"ModernBertForMaskedLM": "bert",
"ModernBertForSequenceClassification": "bert",
"ModernBertModel": "bert",
"NanbeigeForCausalLM": "nanbeige",
"NemotronForCausalLM": "nemotron",
"NemotronHForCausalLM": "nemotron",
"NeoBERT": "bert",
"NeoBERTForSequenceClassification": "bert",
"NeoBERTLMHead": "bert",
"NomicBertModel": "bert",
"OLMoForCausalLM": "olmo",
"Olmo2ForCausalLM": "olmo",
"Olmo3ForCausalLM": "olmo",
"OlmoForCausalLM": "olmo",
"OlmoeForCausalLM": "olmo",
"MuseGlimmerAssistantModel": "muse_glimmer",
"MuseGlimmerForConditionalGeneration": "muse_glimmer",
"OpenELMForCausalLM": "openelm",
"OrionForCausalLM": "orion",
"PLMForCausalLM": "plm",
"PLaMo2ForCausalLM": "plamo",
"PLaMo3ForCausalLM": "plamo",
"PaddleOCRVLForConditionalGeneration": "ernie",
"PanguEmbeddedForCausalLM": "pangu",
"Phi3ForCausalLM": "phi",
"Phi4ForCausalLMV": "phi",
"PhiForCausalLM": "phi",
"PhiMoEForCausalLM": "phi",
"Plamo2ForCausalLM": "plamo",
"Plamo3ForCausalLM": "plamo",
"PlamoForCausalLM": "plamo",
"QWenLMHeadModel": "qwen",
"Qwen2AudioForConditionalGeneration": "qwen",
"Qwen2ForCausalLM": "qwen",
"Qwen2Model": "qwen",
"Qwen2MoeForCausalLM": "qwen",
"Qwen2VLForConditionalGeneration": "qwenvl",
"Qwen2VLModel": "qwenvl",
"Qwen2_5OmniModel": "qwenvl",
"Qwen2_5_VLForConditionalGeneration": "qwenvl",
"Qwen3ASRForConditionalGeneration": "qwen3vl",
"Qwen3ForCausalLM": "qwen",
"Qwen3Model": "qwen",
"Qwen3MoeForCausalLM": "qwen",
"Qwen3NextForCausalLM": "qwen",
"Qwen3OmniMoeForConditionalGeneration": "qwen3vl",
"PocketTTSModel": "pockettts",
"Qwen3TTSForConditionalGeneration": "qwen3tts",
"Qwen3VLForConditionalGeneration": "qwen3vl",
"Qwen3VLMoeForConditionalGeneration": "qwen3vl",
"Qwen3_5ForCausalLM": "qwen",
"Qwen3_5ForConditionalGeneration": "qwen",
"Qwen3_5MoeForCausalLM": "qwen",
"Qwen3_5MoeForConditionalGeneration": "qwen",
"RND1": "qwen",
"RWForCausalLM": "falcon",
"RWKV6Qwen2ForCausalLM": "rwkv",
"RWKV7ForCausalLM": "rwkv",
"RobertaForSequenceClassification": "bert",
"RobertaModel": "bert",
"RuGPT3XLForCausalLM": "gpt2",
"Rwkv6ForCausalLM": "rwkv",
"Rwkv7ForCausalLM": "rwkv",
"RwkvHybridForCausalLM": "rwkv",
"Sarashina2VisionForCausalLM": "sarashina2",
"SarvamMoEForCausalLM": "bailingmoe",
"SeedOssForCausalLM": "olmo",
"SmallThinkerForCausalLM": "smallthinker",
"SmolLM3ForCausalLM": "llama",
"SolarOpenForCausalLM": "glm",
"StableLMEpochForCausalLM": "stablelm",
"StableLmForCausalLM": "stablelm",
"Starcoder2ForCausalLM": "starcoder",
"Step3p5ForCausalLM": "step3",
"StepVLForConditionalGeneration": "step3",
"Step3p7ForConditionalGeneration": "step3",
"T5EncoderModel": "t5",
"T5ForConditionalGeneration": "t5",
"T5WithLMHeadModel": "t5",
"TalkieForCausalLM": "talkie",
"UMT5ForConditionalGeneration": "t5",
"UMT5Model": "t5",
"UltravoxModel": "ultravox",
"UnlimitedOCRForCausalLM": "deepseek",
"VLlama3ForCausalLM": "llama",
"VoxtralForConditionalGeneration": "llama",
"WavTokenizerDec": "wavtokenizer",
"XLMRobertaForSequenceClassification": "bert",
"XLMRobertaModel": "bert",
"XverseForCausalLM": "xverse",
"YoutuForCausalLM": "deepseek",
"YoutuVLForConditionalGeneration": "deepseek",
"modeling_grove_moe.GroveMoeForCausalLM": "grovemoe",
"modeling_sarvam_moe.SarvamMoEForCausalLM": "bailingmoe",
}
MMPROJ_MODEL_MAP: dict[str, str] = {
"AudioFlamingo3ForConditionalGeneration": "ultravox",
"CogVLMForCausalLM": "cogvlm",
"DeepseekOCR2ForCausalLM": "deepseek",
"DeepseekOCRForCausalLM": "deepseek",
"DotsOCRForCausalLM": "dotsocr",
"Exaone4_5_ForConditionalGeneration": "exaone",
"Gemma3ForConditionalGeneration": "gemma",
"Gemma3nForConditionalGeneration": "gemma",
"Gemma4ForConditionalGeneration": "gemma",
"Gemma4UnifiedForConditionalGeneration": "gemma",
"Glm4vForConditionalGeneration": "qwen3vl",
"Glm4vMoeForConditionalGeneration": "qwen3vl",
"Glm5vForConditionalGeneration": "kimivl",
"GlmOcrForConditionalGeneration": "qwen3vl",
"GlmasrModel": "ultravox",
"Granite4VisionForConditionalGeneration": "granite",
"GraniteSpeechForConditionalGeneration": "granite",
"GraniteSpeechPlusForConditionalGeneration": "granite",
"HunYuanVLForConditionalGeneration": "hunyuan",
"Idefics3ForConditionalGeneration": "smolvlm",
"InternVisionModel": "internvl",
"JanusForConditionalGeneration": "januspro",
"KimiK25ForConditionalGeneration": "kimivl",
"KimiVLForConditionalGeneration": "kimivl",
"Lfm2AudioForConditionalGeneration": "lfm2",
"Lfm2VlForConditionalGeneration": "lfm2",
"LightOnOCRForConditionalGeneration": "lighton_ocr",
"Llama4ForConditionalGeneration": "llama4",
"LlavaForConditionalGeneration": "llava",
"MERaLiON2ForConditionalGeneration": "ultravox",
"MiMoV2ForCausalLM": "mimo",
"MiniMaxM3SparseForConditionalGeneration": "minimax",
"MiniCPMV4_6ForConditionalGeneration": "minicpm",
"Mistral3ForConditionalGeneration": "llava",
"NemotronH_Nano_VL_V2": "nemotron",
"MuseGlimmerForConditionalGeneration": "muse_glimmer",
"PaddleOCRVisionModel": "ernie",
"Phi4ForCausalLMV": "phi",
"Qwen2AudioForConditionalGeneration": "ultravox",
"Qwen2VLForConditionalGeneration": "qwenvl",
"Qwen2VLModel": "qwenvl",
"Qwen2_5OmniModel": "qwenvl",
"Qwen2_5_VLForConditionalGeneration": "qwenvl",
"Qwen3ASRForConditionalGeneration": "qwen3vl",
"Qwen3OmniMoeForConditionalGeneration": "qwen3vl",
"PocketTTSModel": "pockettts",
"Qwen3TTSForConditionalGeneration": "qwen3tts",
"Qwen3VLForConditionalGeneration": "qwen3vl",
"Qwen3VLMoeForConditionalGeneration": "qwen3vl",
"Qwen3_5ForConditionalGeneration": "qwen3vl",
"Qwen3_5MoeForConditionalGeneration": "qwen3vl",
"RADIOModel": "nemotron",
"Sarashina2VisionForCausalLM": "sarashina2",
"SmolVLMForConditionalGeneration": "smolvlm",
"StepVLForConditionalGeneration": "step3",
"Step3p7ForConditionalGeneration": "step3",
"UltravoxModel": "ultravox",
"UnlimitedOCRForCausalLM": "deepseek",
"VoxtralForConditionalGeneration": "ultravox",
"YoutuVLForConditionalGeneration": "youtuvl",
}
_TEXT_MODEL_MODULES = sorted(set(TEXT_MODEL_MAP.values()))
_MMPROJ_MODEL_MODULES = sorted(set(MMPROJ_MODEL_MAP.values()))
_loaded_text_modules: set[str] = set()
_loaded_mmproj_modules: set[str] = set()
def load_all_models() -> None:
"""Import all model modules to trigger @ModelBase.register() decorators."""
if len(_loaded_text_modules) != len(_TEXT_MODEL_MODULES):
for module_name in _TEXT_MODEL_MODULES:
if module_name not in _loaded_text_modules:
try:
__import__(f"conversion.{module_name}")
_loaded_text_modules.add(module_name)
except Exception as e:
logger.warning(f"Failed to load model module {module_name}: {e}")
if len(_loaded_mmproj_modules) != len(_MMPROJ_MODEL_MODULES):
for module_name in _MMPROJ_MODEL_MODULES:
if module_name not in _loaded_mmproj_modules:
try:
__import__(f"conversion.{module_name}")
_loaded_mmproj_modules.add(module_name)
except Exception as e:
logger.warning(f"Failed to load model module {module_name}: {e}")
def get_model_class(name: str, mmproj: bool = False) -> Type[ModelBase]:
"""Dynamically import and return a model class by its HuggingFace architecture name."""
relevant_map = MMPROJ_MODEL_MAP if mmproj else TEXT_MODEL_MAP
if name not in relevant_map:
raise NotImplementedError(f"Architecture {name!r} not supported!")
module_name = relevant_map[name]
__import__(f"conversion.{module_name}")
model_type = ModelType.MMPROJ if mmproj else ModelType.TEXT
return ModelBase._model_classes[model_type][name]
def print_registered_models() -> None:
load_all_models()
logger.error("TEXT models:")
for name in sorted(TEXT_MODEL_MAP.keys()):
logger.error(f" - {name}")
logger.error("MMPROJ models:")
for name in sorted(MMPROJ_MODEL_MAP.keys()):
logger.error(f" - {name}")