metadata
tags:
- merge
- mergekit
- lazymergekit
- mlabonne/NeuralBeagle14-7B
base_model:
- mlabonne/NeuralBeagle14-7B
munin-neuralbeagle-7b-density-very-low
munin-neuralbeagle-7b-density-very-low is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: danish-foundation-models/munin-7b-alpha
# No parameters necessary for base model
- model: mlabonne/NeuralBeagle14-7B
parameters:
density: 0.1
weight: 0.6
merge_method: dare_ties
base_model: danish-foundation-models/munin-7b-alpha
parameters:
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "merge-crew/munin-neuralbeagle-7b-density-very-low"
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"])