aashish1904's picture
Upload README.md with huggingface_hub
f561314 verified
|
raw
history blame
No virus
3.23 kB
---
base_model:
- meta-llama/Meta-Llama-3.1-8B-Instruct
- elyza/Llama-3-ELYZA-JP-8B
- nvidia/Llama3-ChatQA-1.5-8B
library_name: transformers
tags:
- mergekit
- merge
language:
- ja
license: llama3
---
![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
# QuantFactory/Llama3.1-ArrowSE-v0.4-GGUF
This is quantized version of [DataPilot/Llama3.1-ArrowSE-v0.4](https://huggingface.co/DataPilot/Llama3.1-ArrowSE-v0.4) created using llama.cpp
# Original Model Card
## 概要 
このモデルはllama3.1-8B-instructをもとに日本語性能を高めることを目的にMergekit&ファインチューニングを用いて作成されました。
meta,ELYZA,nvidiaの皆様に感謝します。
## how to use
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
DEFAULT_SYSTEM_PROMPT = "あなたは誠実で優秀な日本人のアシスタントです。特に指示が無い場合は、常に日本語で回答してください。"
text = "Vtuberとして成功するために大切な5つのことを小学生にでもわかるように教えてください。"
model_name = "DataPilot/Llama3.1-ArrowSE-v0.4"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto",
)
model.eval()
messages = [
{"role": "system", "content": DEFAULT_SYSTEM_PROMPT},
{"role": "user", "content": text},
]
prompt = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
token_ids = tokenizer.encode(
prompt, add_special_tokens=False, return_tensors="pt"
)
with torch.no_grad():
output_ids = model.generate(
token_ids.to(model.device),
max_new_tokens=1200,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
output = tokenizer.decode(
output_ids.tolist()[0][token_ids.size(1):], skip_special_tokens=True
)
print(output)
```
## merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using meta-llama/Meta-Llama-3.1-8B-Instruct as a base.
### Models Merged
The following models were included in the merge:
* [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
* [elyza/Llama-3-ELYZA-JP-8B](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B)
* [nvidia/Llama3-ChatQA-1.5-8B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: meta-llama/Meta-Llama-3.1-8B-Instruct
parameters:
weight: 1
- model: elyza/Llama-3-ELYZA-JP-8B
parameters:
weight: 0.7
- model: nvidia/Llama3-ChatQA-1.5-8B
parameters:
weight: 0.15
merge_method: ties
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
parameters:
normalize: false
dtype: bfloat16
```