metadata
license: cc-by-nc-4.0
tags:
- merge
- mergekit
- lazymergekit
base_model:
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
FrankenMonarch-7B
FrankenMonarch-7B is a merge of the following models using LazyMergekit:
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
- mlabonne/AlphaMonarch-7B
Quantized versions :
🧩 Configuration
dtype: float16
merge_method: passthrough
slices:
- sources:
- model: mlabonne/AlphaMonarch-7B
layer_range: [0,9]
- sources:
- model: mlabonne/AlphaMonarch-7B
layer_range: [5,14]
- sources:
- model: mlabonne/AlphaMonarch-7B
layer_range: [10,19]
- sources:
- model: mlabonne/AlphaMonarch-7B
layer_range: [15,24]
- sources:
- model: mlabonne/AlphaMonarch-7B
layer_range: [20,32]
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/FrankenMonarch-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"])