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---
base_model:
- tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1
- BAAI/Infinity-Instruct-7M-Gen-Llama3_1-8B
library_name: transformers
tags:
- merge
- mergekit
language:
- ja
- en
---
# Llama 3.1 Swallow Gen 8B v0.1
Llama 3.1 Swallow Gen 8B v0.1 is a merge of the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1](https://huggingface.co./tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1)
* [BAAI/Infinity-Instruct-7M-Gen-Llama3_1-8B](https://huggingface.co./BAAI/Infinity-Instruct-7M-Gen-Llama3_1-8B)
## 🧩 Configuration
```yaml
models:
- model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1
# No parameters necessary for base model
- model: BAAI/Infinity-Instruct-7M-Gen-Llama3_1-8B
parameters:
density: 0.5
weight: 1
merge_method: dare_ties
base_model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1
parameters:
int8_mask: true
tokenizer_source: union
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "AELLM/llama-3.1-swallow-gen-8b-v0.1"
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"])
``` |