| # coding=utf-8 | |
| # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. | |
| # | |
| # This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX | |
| # and OPT implementations in this library. It has been modified from its | |
| # original forms to accommodate minor architectural differences compared | |
| # to GPT-NeoX and OPT used by the Meta AI team that trained the model. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """ LLaMA model configuration""" | |
| from transformers import LlamaConfig as HFLlamaConfig | |
| from transformers.utils import logging | |
| logger = logging.get_logger(__name__) | |
| class LlamaConfig(HFLlamaConfig): | |
| model_type = "llama" | |
| def __init__( | |
| self, | |
| mem_id=32001, | |
| mem_freq=50, | |
| mem_top_k=5, | |
| mem_max_seq_len=255, | |
| mem_max_cache_size=None, | |
| **kwargs, | |
| ): | |
| self.mem_id = mem_id | |
| self.mem_freq = mem_freq | |
| self.mem_top_k = mem_top_k | |
| self.mem_max_seq_len = mem_max_seq_len | |
| self.mem_max_cache_size = mem_max_cache_size | |
| super().__init__(**kwargs) | |