jsfs11_-_WestOrcaDPO-7B-GTA-4bits

Quantization made by Richard Erkhov.

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WestOrcaDPO-7B-GTA - bnb 4bits

• Model creator: https://huggingface.co/jsfs11/
• Original model: https://huggingface.co/jsfs11/WestOrcaDPO-7B-GTA/

Original model description:

tags:

• merge
• mergekit
• lazymergekit
• decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
• senseable/WestLake-7B-v2 base_model:
• decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
• senseable/WestLake-7B-v2

---

WestOrcaDPO-7B-GTA

WestOrcaDPO-7B-GTA is a merge of the following models using LazyMergekit:

• decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
• senseable/WestLake-7B-v2

🧩 Configuration

models:
  - model: decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
    parameters:
      density: 0.5
      weight: 0.4
  - model: senseable/WestLake-7B-v2
    parameters:
      density: 0.5
      weight: 0.6
merge_method: task_arithmetic
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: True
  normalize: True
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/WestOrcaDPO-7B-GTA"
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"])