Orpomis-Prime-7B-dare
Orpomis-Prime-7B-dare is a merge of the following models using Mergekit:
🧩 Configuration
models:
- model: kaist-ai/mistral-orpo-beta
parameters:
density: 0.5
weight: 0.6
# No parameters necessary for base model
- model: NousResearch/Hermes-2-Pro-Mistral-7B
parameters:
density: 0.5
weight: 0.4
merge_method: dare_ties
base_model: kaist-ai/mistral-orpo-beta
parameters:
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "saucam/Orpomis-Prime-7B-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"])
Sample Run
<|user|>
Beth bakes 4, or 2 dozen batches of cookies in a week. If these cookies are shared amongst 16 people equally, how many cookies does each person consume?</s>
<|assistant|>
If Beth bakes 4, or 2 dozen batches of cookies in a week, then she bakes a total of 2 x 4 = 8 dozen cookies.
If these cookies are shared amongst 16 people equally, each person would consume 8 dozen cookies / 16 people = 0.5 dozen cookies.
Since there are 12 cookies in a dozen, each person would consume 0.5 dozen cookies * 12 cookies/dozen = 6 cookies.
So, each person consumes 6 cookies.