metadata

license: cc-by-nc-4.0
tags:
  - merge
  - mergekit
base_model:
  - seyf1elislam/WestKunai-Hermes-7b
  - seyf1elislam/WestKunai-Hermes-7b
  - seyf1elislam/WestKunai-Hermes-7b
  - seyf1elislam/WestKunai-Hermes-7b
  - seyf1elislam/WestKunai-Hermes-7b

WestKunai-Hermes-10.7b-test

Replicate the configuration utilized in the froggeric/WestLake-10.7B-v2 model to extend the WestKunai-Hermes-7b model to 10.7b.

Merge Details

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
    - model: seyf1elislam/WestKunai-Hermes-7b
      layer_range: [0,9]
  - sources:
    - model: seyf1elislam/WestKunai-Hermes-7b
      layer_range: [5,14]
  - sources:
    - model: seyf1elislam/WestKunai-Hermes-7b
      layer_range: [10,19]
  - sources:
    - model: seyf1elislam/WestKunai-Hermes-7b
      layer_range: [15,24]
  - sources:
    - model: seyf1elislam/WestKunai-Hermes-7b
      layer_range: [20,32]
merge_method: passthrough
dtype: bfloat16

Usage Example

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "seyf1elislam/WestKunai-Hermes-10.7b-test"
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"])