metadata

base_model:
  - tokyotech-llm/Swallow-MS-7b-v0.1
  - mistralai/Mistral-7B-v0.1
  - nitky/Flavor-7b
  - stabilityai/japanese-stablelm-base-gamma-7b
library_name: transformers
tags:
  - mergekit
  - merge
language:
  - ja
  - en
pipeline_tag: text-generation
license: apache-2.0

Oumuamua-7b-base

This is a merge of pre-trained language models created using mergekit.

Output example

Input text

日本で最も高い山の名前は

Output text

日本で最も高い山の名前は、富士山。
その標高は3776メートル。
世界でも20位以内に入る高さを誇る。
その富士山の麓にあるのが、静岡県富士市。
富士市は、富士山の麓にあるため、観光地としても有名である。
富士山の麓にあることから、富士市は観光地としても有名である。
富士山を眺めることができるスポットが多く、特に富士市の中心部から見る富士山は、その美しさから「日本一の眺望」と言われている。

Test environment

This model was tested using text-generation-webui. I use preset min_p and Null preset with temperature=0.3 for Generation.

Usage

Use the base model

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "nitky/Oumuamua-7b-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)

model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
prompt = "日本で最も高い山の名前は"
input_ids = tokenizer.encode(
    prompt,
    add_special_tokens=False,
    return_tensors="pt"
)
tokens = model.generate(
    input_ids.to(device=model.device),
    max_new_tokens=256,
    do_sample=True,
    temperature=0.3
)

out = tokenizer.decode(tokens[0], skip_special_tokens=True)
print(out)

Merge Details

Merge Method

This model was merged using the Model Stock merge method using tokyotech-llm/Swallow-MS-7b-v0.1 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: task_arithmetic
base_model: mistralai/Mistral-7B-v0.1
models:
  - model: tokyotech-llm/Swallow-MS-7b-v0.1
    parameters:
      weight:
      - filter: embed_tokens
        value: 1.0
      - value: 0
dtype: bfloat16
tokenizer_source: model:tokyotech-llm/Swallow-MS-7b-v0.1
name: Mistral-7B-v0.1-VE-Swallow-MS
---
merge_method: task_arithmetic
base_model: nitky/Flavor-7b # private model
models:
  - model: tokyotech-llm/Swallow-MS-7b-v0.1
    parameters:
      weight:
      - filter: embed_tokens
        value: 1.0
      - value: 0
dtype: bfloat16
tokenizer_source: model:tokyotech-llm/Swallow-MS-7b-v0.1
name: Flavor-7b-VE-Swallow-MS
---
merge_method: task_arithmetic
base_model: stabilityai/japanese-stablelm-base-gamma-7b
models:
  - model: tokyotech-llm/Swallow-MS-7b-v0.1
    parameters:
      weight:
      - filter: embed_tokens
        value: 1.0
      - value: 0
dtype: bfloat16
tokenizer_source: model:tokyotech-llm/Swallow-MS-7b-v0.1
name: japanese-stablelm-base-gamma-7b-VE-Swallow-MS
---
merge_method: task_arithmetic
base_model: Mistral-7B-v0.1-VE-Swallow-MS
models:
  - model: tokyotech-llm/Swallow-MS-7b-v0.1
    parameters:
      weight: 1.0
  - model: Flavor-7b-VE-Swallow-MS
    parameters:
      weight: 0.5
  - model: japanese-stablelm-base-gamma-7b-VE-Swallow-MS
    parameters:
      weight: -0.5
dtype: bfloat16
name: Oumuamua-7b-base-preset
---
merge_method: model_stock
base_model: Mistral-7B-v0.1-VE-Swallow-MS
models:
  - model: tokyotech-llm/Swallow-MS-7b-v0.1
  - model: Oumuamua-7b-base-preset
dtype: bfloat16
name: Oumuamua-7b-base