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---
base_model:
- Dampfinchen/Llama-3.1-8B-Ultra-Instruct
tags:
- merge
- mergekit
- Undi95/Meta-Llama-3.1-8B-Claude
- Dampfinchen/Llama-3.1-8B-Ultra-Instruct
license: llama3.1
language:
- en
- de
---
# llama3.1-8b-spaetzle-v59
llama3.1-8b-spaetzle-v59 is a dare ties merge of the models
* [Undi95/Meta-Llama-3.1-8B-Claude](https://huggingface.co/Undi95/Meta-Llama-3.1-8B-Claude)
* [Dampfinchen/Llama-3.1-8B-Ultra-Instruct](https://huggingface.co/Dampfinchen/Llama-3.1-8B-Ultra-Instruct)
EQ-Bench v2_de: 67.38 (171/171) (which is not bad...) with q4 quants: [cstr/llama3.1-8b-spaetzle-v59-GGUF](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v59-GGUF/)
## 🧩 Configuration
```yaml
models:
- model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
# no parameters necessary for base model
- model: Undi95/Meta-Llama-3.1-8B-Claude
parameters:
density: 0.65
weight: 0.4
merge_method: dare_ties
base_model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
parameters:
int8_mask: true
dtype: bfloat16
random_seed: 0
tokenizer_source: base
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "cstr/llama3.1-8b-spaetzle-v59"
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"])
``` |