metadata
tags:
- merge
- mergekit
- lazymergekit
- Kaoeiri/L3MaidRPKraiKei-V1.6-8B
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.2
base_model:
- Kaoeiri/L3MaidRPKraiKei-V1.6-8B
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.2
L3MaidRPKraiKei-V1.65-8B
L3MaidRPKraiKei-V1.65-8B is a merge of the following models using LazyMergekit:
Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
🧩 Configuration
models:
- model: Kaoeiri/L3MaidRPKraiKei-V1.6-8B
parameters:
density: .5
weight: 1
- model: openlynn/Llama-3-Soliloquy-8B-v2
parameters:
density: .35
weight: .4
- model: Sao10K/L3-8B-Stheno-v3.2
parameters:
density: .5
weight: .7
merge_method: ties
base_model: mlabonne/NeuralDaredevil-8B-abliterated
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kaoeiri/L3MaidRPKraiKei-V1.65-8B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])