---
base_model:
- inceptionai/jais-family-590m
- inceptionai/jais-family-590m
tags:
- merge
- mergekit
- lazymergekit
- inceptionai/jais-family-590m
---

# Jais-590m-merged

Jais-590m-merged is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [inceptionai/jais-family-590m](https://huggingface.co/inceptionai/jais-family-590m)
* [inceptionai/jais-family-590m](https://huggingface.co/inceptionai/jais-family-590m)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: inceptionai/jais-family-590m
        layer_range: [0, 18]
      - model: inceptionai/jais-family-590m
        layer_range: [0, 18]
merge_method: slerp
base_model: inceptionai/jais-family-590m
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
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Solshine/Jais-590m-merged"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model, trust_remote_code=True)

# Manually apply a basic chat template since it's not provided by the model
def custom_chat_template(messages):
    chat_prompt = ""
    for message in messages:
        role = message["role"]
        content = message["content"]
        chat_prompt += f"{role}: {content}\n"
    return chat_prompt

prompt = custom_chat_template(messages)

pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
    trust_remote_code=True,
)

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"])
```