Text Generation
PEFT
Safetensors
English
lora
llama
creative-writing
prose-style
roleplay
conversational
Instructions to use darthcrawl/artifex-rp-orpheus-llama-3.1-8b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use darthcrawl/artifex-rp-orpheus-llama-3.1-8b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "darthcrawl/artifex-rp-orpheus-llama-3.1-8b-lora") - Notebooks
- Google Colab
- Kaggle
artifex-rp-orpheus-llama-3.1-8b-lora
LoRA adapter for meta-llama/Llama-3.1-8B-Instruct. For most users the merged model at darthcrawl/artifex-rp-orpheus-llama-3.1-8b is easier to use.
Apply
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
base_id = "meta-llama/Llama-3.1-8B-Instruct"
adapter_id = "darthcrawl/artifex-rp-orpheus-llama-3.1-8b-lora"
tok = AutoTokenizer.from_pretrained(base_id, use_fast=True)
model = AutoModelForCausalLM.from_pretrained(
base_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
model = PeftModel.from_pretrained(model, adapter_id)
Sampling settings
| Parameter | Value |
|---|---|
| temperature | 0.85 |
| top_p | 0.95 |
| repetition_penalty | 1.1 |
System prompt
Write in vivid, restrained, intelligent prose. Concrete sensory detail.
Never pretentious. Tension carries more weight than description.
Match the user's energy and length.
License
Same license as the base model (meta-llama/Llama-3.1-8B-Instruct). Apache 2.0 for the training pipeline.
- Downloads last month
- 4
Model tree for darthcrawl/artifex-rp-orpheus-llama-3.1-8b-lora
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct