🦾 Supported models

Base versions

Model	Model Key	LoRA	INT8	LoRA + INT8	LoRA + INT4
BLOOM 1.1B	bloom	✅	✅	✅	✅
Cerebras 1.3B	cerebras	✅	✅	✅	✅
DistilGPT-2	distilgpt2	✅	✅	✅	✅
Falcon 7B	falcon	✅	✅	✅	✅
Galactica 6.7B	galactica	✅	✅	✅	✅
GPT-J 6B	gptj	✅	✅	✅	✅
GPT-2	gpt2	✅	✅	✅	✅
LLaMA 7B	llama	✅	✅	✅	✅
LLaMA2	llama2	✅	✅	✅	✅
MiniMaxM2	minimax_m2	✅	✅	✅	✅
Qwen3 0.6B	qwen3_0_6b	✅	✅	✅	✅
OPT 1.3B	opt	✅	✅	✅	✅

Memory-efficient versions

The above mentioned are the base variants of the LLMs. Below are the templates to get their LoRA, INT8, INT8 + LoRA and INT4 + LoRA versions.

Version	Template
LoRA	<model_key>_lora
INT8	<model_key>_int8
INT8 + LoRA	<model_key>_lora_int8

INT4 Precision model versions

In order to load any model's INT4+LoRA version, you will need to make use of GenericLoraKbitModel class from xturing.models. Below is how to use it:

from xturing.models import GenericLoraKbitModel
model = GenericLoraKbitModel('/path/to/model')

The /path/to/model can be replaced with you local directory or any HuggingFace library model like facebook/opt-1.3b.