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cc7200bf12
* move conversion code to a dedicated conversion directory and split the files akin to the src/models architecture --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
from __future__ import annotations
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from typing import Callable, TYPE_CHECKING
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if TYPE_CHECKING:
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from torch import Tensor
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from .base import ModelBase, TextModel, gguf, logger
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@ModelBase.register("WavTokenizerDec")
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class WavTokenizerDecModel(TextModel):
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model_arch = gguf.MODEL_ARCH.WAVTOKENIZER_DEC
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@classmethod
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def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
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name, gen = item
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if \
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name.endswith("codebook.cluster_size") or \
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name.endswith("codebook.embed_avg") or \
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name.endswith("codebook.inited"):
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logger.debug(f"Skipping {name!r}")
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return None
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return super().filter_tensors(item)
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def set_vocab(self):
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self._set_vocab_none()
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def set_gguf_parameters(self):
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super().set_gguf_parameters()
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self.gguf_writer.add_vocab_size (self.hparams["vocab_size"])
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self.gguf_writer.add_features_length (self.hparams["n_embd_features"])
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self.gguf_writer.add_feed_forward_length(self.hparams["n_ff"])
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self.gguf_writer.add_group_norm_eps (self.hparams["group_norm_epsilon"])
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self.gguf_writer.add_group_norm_groups (self.hparams["group_norm_groups"])
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self.gguf_writer.add_posnet_embedding_length(self.hparams["posnet"]["n_embd"])
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self.gguf_writer.add_posnet_block_count (self.hparams["posnet"]["n_layer"])
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self.gguf_writer.add_convnext_embedding_length(self.hparams["convnext"]["n_embd"])
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self.gguf_writer.add_convnext_block_count (self.hparams["convnext"]["n_layer"])
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self.gguf_writer.add_causal_attention(False)
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