transformers safetensors llama text-generation merge mergekit lazymergekit deepapaikar/Llama_SCplusQA_10epochs codegood/Mistral_Latest_new base_model:deepapaikar/Llama_SCplusQA_10epochs base_model:codegood/Mistral_Latest_new autotrain_compatible endpoints_compatible text-generation-inference region:us
---
tags:
- merge
- mergekit
- lazymergekit
- deepapaikar/Llama_SCplusQA_10epochs
- codegood/Mistral_Latest_new
base_model:
- deepapaikar/Llama_SCplusQA_10epochs
- codegood/Mistral_Latest_new
---

# llama_mistral

llama_mistral is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [deepapaikar/Llama_SCplusQA_10epochs](https://huggingface.co/deepapaikar/Llama_SCplusQA_10epochs)
* [codegood/Mistral_Latest_new](https://huggingface.co/codegood/Mistral_Latest_new)

## 🧩 Configuration

```yaml
models:
  - model: deepapaikar/Llama_SCplusQA_10epochs
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: codegood/Mistral_Latest_new
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: ties
base_model: deepapaikar/Llama_SCplusQA_10epochs
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "deepapaikar/llama_mistral"
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"])
```