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Types & classes26 in github.com/GCYZSL/MoLA

⨍ Functions 226◇ Types & classes 26 ↳ Endpoints 1

↓ 3 callersClassLlamaModel

Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`LlamaDecoderLayer`] Args: config: LlamaConfig

src/mola_modeling_llama_hacked.py:656

↓ 3 callersClassLlamaRMSNorm

src/mola_modeling_llama_hacked.py:164

↓ 2 callersClassLoraConfig

This is the configuration class to store the configuration of a [`LoraModel`]. Args: r (`int`): Lora attention dimension. ta

src/mola_lora_hacked.py:31

↓ 2 callersClassPrompter

utils/prompter.py:10

↓ 2 callersClassTrainer

Trainer is a simple but feature-complete training and eval loop for PyTorch, optimized for 🤗 Transformers. Args: model ([`PreTrained

src/mola_trainer_hacked.py:211

↓ 1 callersClassLinear_MoE

src/mola_lora_hacked.py:763

↓ 1 callersClassLlamaAttention

Multi-headed attention from 'Attention Is All You Need' paper

src/mola_modeling_llama_hacked.py:277

↓ 1 callersClassLlamaDecoderLayer

src/mola_modeling_llama_hacked.py:455

↓ 1 callersClassLlamaMLP

src/mola_modeling_llama_hacked.py:231

↓ 1 callersClassLlamaRotaryEmbedding

src/mola_modeling_llama_hacked.py:184

↓ 1 callersClassPeftModel

Base model encompassing various Peft methods. Args: model ([`~transformers.PreTrainedModel`]): The base transformer model used for P

src/mola_peft_model_hacked.py:188

↓ 1 callersClassPrompter

evaluation_scienceqa.py:31

ClassIteratorize

Transforms a function that takes a callback into a lazy iterator (generator).

utils/callbacks.py:25

ClassLlamaForCausalLM

src/mola_modeling_llama_hacked.py:955

ClassLlamaForCausalLM_d

src/mola_modeling_llama_hacked.py:1143

ClassLlamaForSequenceClassification

src/mola_modeling_llama_hacked.py:1387

ClassLlamaPreTrainedModel

src/mola_modeling_llama_hacked.py:569

src/mola_lora_hacked.py:543

ClassLoraMoE_Layer

src/mola_lora_hacked.py:642

Creates Low Rank Adapter (Lora) model from a pretrained transformers model. Args: model ([`~transformers.PreTrainedModel`]): The mod

src/mola_lora_hacked.py:98

ClassPeftModelForCausalLM

Peft model for causal language modeling. Args: model ([`~transformers.PreTrainedModel`]): Base transformer model. peft_confi

src/mola_peft_model_hacked.py:911

ClassPeftModelForQuestionAnswering

Peft model for extractive question answering. Args: model ([`~transformers.PreTrainedModel`]): Base transformer model. peft_

src/mola_peft_model_hacked.py:1482

ClassPeftModelForSeq2SeqLM

Peft model for sequence-to-sequence language modeling. Args: model ([`~transformers.PreTrainedModel`]): Base transformer model.

src/mola_peft_model_hacked.py:1080

ClassPeftModelForSequenceClassification

Peft model for sequence classification tasks. Args: model ([`~transformers.PreTrainedModel`]): Base transformer model. peft_

src/mola_peft_model_hacked.py:723

ClassPeftModelForTokenClassification

Peft model for token classification tasks. Args: model ([`~transformers.PreTrainedModel`]): Base transformer model. peft_con

src/mola_peft_model_hacked.py:1310

utils/callbacks.py:15