README.md

---
tags:
- merge
- mergekit
- lazymergekit
- cognitivecomputations/samantha-mistral-7b
- CorticalStack/shadow-clown-7B-dare
- yam-peleg/Experiment26-7B
base_model:
- cognitivecomputations/samantha-mistral-7b
- CorticalStack/shadow-clown-7B-dare
- yam-peleg/Experiment26-7B
license: apache-2.0
---

# yam-sam-7B

yam-sam-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [cognitivecomputations/samantha-mistral-7b](https://huggingface.co/cognitivecomputations/samantha-mistral-7b)
* [CorticalStack/shadow-clown-7B-dare](https://huggingface.co/CorticalStack/shadow-clown-7B-dare)
* [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)

## 🧩 Configuration

```yaml
models:
  - model: yam-peleg/Experiment27-7B
    # No parameters necessary for base model
  - model: cognitivecomputations/samantha-mistral-7b
    parameters:
      weight: 0.3
      density: 0.8
  - model: CorticalStack/shadow-clown-7B-dare
    parameters:
      weight: 0.1
      density: 0.8
  - model: yam-peleg/Experiment26-7B
    parameters:
      weight: 0.6
      density: 0.8
merge_method: dare_ties
base_model: yam-peleg/Experiment27-7B
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0

```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/yam-sam-7B"
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"])
```