README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - meta-llama/Meta-Llama-3-8B-Instruct
  - meta-llama/Meta-Llama-3-8B-Instruct
  - PruneMe
base_model:
  - meta-llama/Meta-Llama-3-8B-Instruct
  - meta-llama/Meta-Llama-3-8B-Instruct

meta-LLama3-8b-PruneME-TEST-22_30

This model was pruned after being analyzed with PruneMe

INFO:root:Layer 22 to 30 has the minimum average distance of 0.26598974609375. Consider examining this layer more closely for potential optimization or removal.

meta-LLama3-8b-PruneME-TEST-22_30 is a merge of the following models using LazyMergekit:

• meta-llama/Meta-Llama-3-8B-Instruct
• meta-llama/Meta-Llama-3-8B-Instruct

🧩 Configuration

slices:
  - sources:
      - model: meta-llama/Meta-Llama-3-8B-Instruct
        layer_range: [0, 22]
  - sources:
      - model: meta-llama/Meta-Llama-3-8B-Instruct
        layer_range: [30,32]
merge_method: passthrough
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/meta-LLama3-8b-PruneME-TEST-22_30"
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"])