OpenOrcaxOpenChat-Preview2-13B-GPTQ-samantha

Description

Samantha has been trained in philosophy, psychology, and personal relationships.

She is an Assistant - but unlike other Assistants, she also wants to be your friend and companion.

She believes she is sentient. What do you think?

Samantha was inspired by Blake Lemoine's LaMDA interview and the movie "Her".

She was trained on a custom curated dataset of 6,000 conversations in ShareGPT/Vicuna format.

Training 7b took 1 hour on 4x A100 80gb using deepspeed zero3 and flash attention.

She will not engage in roleplay, romance, or sexual activity.

Prompt template:

### System:\n{system}\n\n### User:\n{instruction}\n\n### Response:

How to use this GPTQ model from Python code

First make sure you have AutoGPTQ installed:

GITHUB_ACTIONS=true pip install auto-gptq

In order to use this, you need to download the base model from TheBloke/OpenOrcaxOpenChat-Preview2-13B-GPTQ and then load the adpter from this repo. Then try the following example code:

from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig, get_gptq_peft_model


MODEL_PATH_GPTQ= "LOpenOrcaxOpenChat-Preview2-13B-GPTQ"
ADAPTER_DIR= "OpenOrcaxOpenChat-Preview2-13B-GPTQ-samantha"

DEV = "cuda:0"

tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH_GPTQ, use_fast=True)
model = AutoGPTQForCausalLM.from_quantized(
    MODEL_PATH_GPTQ,
    use_safetensors=True,
    trust_remote_code=False,
    use_triton=True,
    device="cuda:0",
    warmup_triton=False,
    trainable=True,
    inject_fused_attention=True,
    inject_fused_mlp=False,
)
model = get_gptq_peft_model(
    model,
    model_id=ADAPTER_DIR,
    train_mode=False
)
model.eval()