README.md

metadata

base_model:
  - ihughes15234/phi35_tictactoe_dpo5epoch_v7
  - ihughes15234/phi35_pd_dpo10epoch_1200
tags:
  - merge
  - mergekit
  - lazymergekit
  - ihughes15234/phi35_tictactoe_dpo5epoch_v7
  - ihughes15234/phi35_pd_dpo10epoch_1200
  - text-generation-inference

phi_35_ttt_pd_merge_Dare_Ties

phi_35_ttt_pd_merge_Dare_Ties is a merge of the following models using LazyMergekit:

• ihughes15234/phi35_tictactoe_dpo5epoch_v7
• ihughes15234/phi35_pd_dpo10epoch_1200

🧩 Configuration

models:
  - model: ihughes15234/phi35_tictactoe_dpo5epoch_v7
    parameters:
      density: 0.5
      weight: 0.5
  - model: ihughes15234/phi35_pd_dpo10epoch_1200
    parameters:
      density: 0.5
      weight: 0.5
merge_method: dare_ties
base_model: ihughes15234/Phi-3.5-mini-instruct_unslothcpy
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "ihughes15234/phi_35_ttt_pd_merge_Dare_Ties"
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"])