metadata
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Meta-Llama-3-8B-Instruct
base_model:
- NousResearch/Meta-Llama-3-8B-Instruct
mix-llama-3-8B-inst-line
mix-llama-3-8B-inst-line is a merge of the following models using LazyMergekit:
🧩 Configuration
dtype: bfloat16
merge_method: linear
slices:
- sources:
- layer_range: [0, 16] # Assuming the first half of the model is more general and can be reduced more
model: NousResearch/Meta-Llama-3-8B-Instruct
parameters:
weight: 0.5 # Reduce the weight of the first half to make room for the second half
- layer_range: [16, 32] # Assuming the second half of the model is more specialized and can be reduced less
model: NousResearch/Meta-Llama-3-8B-Instruct
parameters:
weight: 0.5 # Maintain the weight of the second half
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "JoPmt/mix-llama-3-8B-inst-line"
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"])