metadata
tags:
- merge
- mergekit
- lazymergekit
- Nexusflow/Starling-LM-7B-beta
- timpal0l/Mistral-7B-v0.1-flashback-v2-instruct
- mlabonne/NeuralBeagle14-7B
base_model:
- Nexusflow/Starling-LM-7B-beta
- timpal0l/Mistral-7B-v0.1-flashback-v2-instruct
- mlabonne/NeuralBeagle14-7B
SwedishBeagleDare
SwedishBeagleDare is a merge of the following models using LazyMergekit:
- Nexusflow/Starling-LM-7B-beta
- timpal0l/Mistral-7B-v0.1-flashback-v2-instruct
- mlabonne/NeuralBeagle14-7B
🧩 Configuration
models:
- model: Nexusflow/Starling-LM-7B-beta
parameters:
weight: 0.5
- model: timpal0l/Mistral-7B-v0.1-flashback-v2-instruct
parameters:
weight: 0.5
- model: mlabonne/NeuralBeagle14-7B
parameters:
weight: 0.5
merge_method: task_arithmetic
base_model: mlabonne/NeuralBeagle14-7B
parameters:
int8_mask: 1.0
normalize: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Knobi3/SwedishBeagleDare"
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"])