metadata
base_model:
- m-a-p/neo_7b
tags:
- merge
- mergekit
- lazymergekit
- m-a-p/neo_7b
Neo_7b-merge1
Neo_7b-merge1 is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: m-a-p/neo_7b
layer_range: [0, 27] # 28 layers (0-27)
merge_method: slerp
base_model: m-a-p/neo_7b
parameters:
t:
- filter: self_attn
value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
0.5, 0.5, 0.5, 0.75]
- filter: mlp
value: [0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75, 0.5, 0.5, 0.5, 0.75,
0.5, 0.5, 0.5, 0.75]
- value: 0.5 # Default value for other components
dtype: bfloat16
output_path: ./merged_reduced_neo_7b
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "DewEfresh/Neo_7b-merge1"
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"])