models:
  - model : bigcode/starcoder2-3b
    parameters:
      density: 0.5 # density gradient
      weight: 1
  - model: TechxGenus/starcoder2-3b-instruct
    parameters:
      density: 0.5
      weight: 1 # weight gradient
tokenizer_source: union
merge_method: ties
base_model: bigcode/starcoder2-3b
parameters:
  normalize: true
  int8_mask: true
dtype: float16

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "choprahetarth/tinyllama-merged"
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"])