---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- Weyaxi/Einstein-v5-v0.2-7B
- argilla/CapybaraHermes-2.5-Mistral-7B
base_model:
- Weyaxi/Einstein-v5-v0.2-7B
- argilla/CapybaraHermes-2.5-Mistral-7B
---

# J.O.S.I.E.3-Beta10-7B-slerp

J.O.S.I.E.3-Beta10-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Weyaxi/Einstein-v5-v0.2-7B](https://huggingface.co/Weyaxi/Einstein-v5-v0.2-7B)
* [argilla/CapybaraHermes-2.5-Mistral-7B](https://huggingface.co/argilla/CapybaraHermes-2.5-Mistral-7B)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: Weyaxi/Einstein-v5-v0.2-7B
        layer_range: [0, 32]
      - model: argilla/CapybaraHermes-2.5-Mistral-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: argilla/CapybaraHermes-2.5-Mistral-7B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16
```

## Evaluation

```json
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        "mc1": 0.39657282741738065,
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        "mc2": 0.5688038233837539,
        "mc2_stderr": 0.015263125204118244
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        "acc_norm_stderr": 0.014070265519268802
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    "harness|hellaswag|10": {
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        "acc_norm": 0.8378809002190799,
        "acc_norm_stderr": 0.0036780679944244735
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    "harness|hendrycksTest-anatomy|5": {
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        "acc_norm_stderr": 0.0421850621536888
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    "harness|hendrycksTest-astronomy|5": {
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    "harness|hendrycksTest-econometrics|5": {
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    "harness|hendrycksTest-public_relations|5": {
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    "harness|hendrycksTest-security_studies|5": {
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    "harness|hendrycksTest-sociology|5": {
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    "harness|hendrycksTest-us_foreign_policy|5": {
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    "harness|hendrycksTest-world_religions|5": {
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    "harness|truthfulqa:mc|0": {
        "mc1": 0.39657282741738065,
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        "mc2": 0.5688038233837539,
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    "harness|winogrande|5": {
        "acc": 0.7963693764798737,
        "acc_stderr": 0.011317798781626918
    },
    "harness|gsm8k|5": {
        "acc": 0.6103108415466262,
        "acc_stderr": 0.01343312323611072
    }
}
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Isaak-Carter/J.O.S.I.E.3-Beta10-7B-slerp"
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"])
```