SomeModelsMerge-7b
SomeModelsMerge-7b is a merge of the following models using LazyMergekit:
- liminerity/M7-7b
- Kukedlc/NeuralSirKrishna-7b
- Kukedlc/MyModelsMerge-7b
- AurelPx/Percival_01-7b-slerp
- MatthieuJ/Jason1903_SLERP
- MTSAIR/multi_verse_model
- Gille/StrangeMerges_30-7B-slerp
- chihoonlee10/T3Q-Mistral-Orca-Math-DPO
- yam-peleg/Experiment28-7B
- mlabonne/UltraMerge-7B
🧩 Configuration
models:
- model: liminerity/M7-7b
# no parameters necessary for base model
- model: liminerity/M7-7b
parameters:
weight: 0.2
density: 0.88
- model: Kukedlc/NeuralSirKrishna-7b
parameters:
weight: 0.1
density: 0.66
- model: Kukedlc/MyModelsMerge-7b
parameters:
weight: 0.1
density: 0.66
- model: AurelPx/Percival_01-7b-slerp
parameters:
weight: 0.1
density: 0.33
- model: MatthieuJ/Jason1903_SLERP
parameters:
weight: 0.1
density: 0.33
- model: MTSAIR/multi_verse_model
parameters:
weight: 0.1
density: 0.66
- model: Gille/StrangeMerges_30-7B-slerp
parameters:
weight: 0.1
density: 0.55
- model: chihoonlee10/T3Q-Mistral-Orca-Math-DPO
parameters:
weight: 0.1
density: 0.22
- model: yam-peleg/Experiment28-7B
parameters:
weight: 0.1
density: 0.44
- model: mlabonne/UltraMerge-7B
parameters:
weight: 0.1
density: 0.77
merge_method: dare_ties
base_model: liminerity/M7-7b
parameters:
int8_mask: true
normalize: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/SomeModelsMerge-7b"
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"])