llama.cpp/conversion/plm.py

from __future__ import annotations

from .base import ModelBase, TextModel, gguf


@ModelBase.register("PLMForCausalLM")
class PLMModel(TextModel):
    model_arch = gguf.MODEL_ARCH.PLM

    def set_vocab(self):
        self._set_vocab_gpt2()

    def set_gguf_parameters(self):
        super().set_gguf_parameters()
        hparams = self.hparams
        self.gguf_writer.add_vocab_size(hparams["vocab_size"])
        self.gguf_writer.add_kv_lora_rank(hparams["kv_lora_rank"])
        self.gguf_writer.add_key_length(hparams["qk_nope_head_dim"] + hparams["qk_rope_head_dim"])
        self.gguf_writer.add_value_length(hparams["v_head_dim"])
        self.gguf_writer.add_rope_dimension_count(hparams["qk_rope_head_dim"])

    def prepare_tensors(self):
        super().prepare_tensors()