BabyHydra-dare
𧩠Configuration
models:
- model: OpenPipe/mistral-ft-optimized-1218
# No parameters necessary for base model
- model: WizardLMTeam/WizardMath-7B-V1.1
parameters:
density: 0.53
weight: 0.4
- model: abacusai/Slerp-CM-mist-dpo
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: OpenPipe/mistral-ft-optimized-1218
parameters:
int8_mask: true
normalize: true
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jS84/BabyHydra-dare"
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"])
Thanks to MergeKit and Lazymergekit for the inspiration!
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