metadata

base_model:
  - yuvraj17/Llama-3-8B-spectrum-25
  - ruggsea/Llama3-stanford-encyclopedia-philosophy-QA
  - arcee-ai/Llama-3.1-SuperNova-Lite
tags:
  - merge
  - mergekit
  - lazymergekit
  - yuvraj17/Llama-3-8B-spectrum-25
  - ruggsea/Llama3-stanford-encyclopedia-philosophy-QA
  - arcee-ai/Llama-3.1-SuperNova-Lite

Llama3-8B-SuperNova-Spectrum-dare_ties

Llama3-8B-SuperNova-Spectrum-dare_ties is a merge of the following models using LazyMergekit:

🧩 Configuration

models:
  - model: NousResearch/Meta-Llama-3-8B
    # No parameters necessary for base model
  - model: yuvraj17/Llama-3-8B-spectrum-25
    parameters:
      density: 0.56
      weight: 0.12
  - model: ruggsea/Llama3-stanford-encyclopedia-philosophy-QA
    parameters:
      density: 0.56
      weight: 0.12
  - model: arcee-ai/Llama-3.1-SuperNova-Lite
    parameters:
      density: 0.58
      weight: 0.55
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "yuvraj17/Llama3-8B-SuperNova-Spectrum-dare_ties"
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"])