slices:
  - sources:
    - model: meta-llama/Meta-Llama-3-8B-Instruct
      layer_range: [0, 24]
  - sources:
    - model: meta-llama/Meta-Llama-3-8B-Instruct
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/FrankenLlama-3-12B"
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"])

mlabonne/FrankenLlama-3-12B-Instruct

FrankenLlama-3-12B

🧩 Configuration

💻 Usage

mlabonne/
FrankenLlama-3-12B-Instruct