README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - macadeliccc/WestLake-7B-v2-laser-truthy-dpo
  - cgato/Thespis-CurtainCall-7b-v0.2.2
base_model:
  - macadeliccc/WestLake-7B-v2-laser-truthy-dpo
  - cgato/Thespis-CurtainCall-7b-v0.2.2

TheSpissInWestLake-7B-V1

TheSpissInWestLake-7B-V1 is a merge of the following models using LazyMergekit:

Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.

• macadeliccc/WestLake-7B-v2-laser-truthy-dpo
• cgato/Thespis-CurtainCall-7b-v0.2.2

🧩 Configuration

models:
  - model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
    parameters:
      density: .5
      weight: 1
  - model: cgato/Thespis-CurtainCall-7b-v0.2.2
    parameters:
      density: .5
      weight: .7
merge_method: ties
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kaoeiri/TheSpissInWestLake-7B-V1"
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"])