metadata

base_model:
  - NousResearch/Hermes-2-Theta-Llama-3-8B
  - mlabonne/NeuralDaredevil-8B-abliterated
  - cognitivecomputations/dolphin-2.9.3-llama-3-8b
tags:
  - merge
  - mergekit
  - lazymergekit
  - NousResearch/Hermes-2-Theta-Llama-3-8B
  - mlabonne/NeuralDaredevil-8B-abliterated
  - cognitivecomputations/dolphin-2.9.3-llama-3-8b

NeuralPipe-7B-slerp

NeuralPipe-7B-slerp is a merge of the following models using LazyMergekit:

🧩 Configuration

models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
  - model: NousResearch/Hermes-2-Theta-Llama-3-8B
    parameters:
      density: 0.53
      weight: 0.4
  - model: mlabonne/NeuralDaredevil-8B-abliterated
    parameters:
      density: 0.56
      weight: 0.4
  - model: cognitivecomputations/dolphin-2.9.3-llama-3-8b
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Trisert/NeuralPipe-7B-slerp"
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"])