transformers safetensors mistral text-generation conversational autotrain_compatible endpoints_compatible text-generation-inference region:us
---
{}
---
---
    license: cc-by-nc-4.0
    base_model:
    - mlabonne/NeuralBeagle14-7B
    - FelixChao/WestSeverus-7B-DPO-v2
    tags:
    - merge
    - mergekit
    - lazymergekit
    ---

    # shadowml/WestBeagle-7B-gen2

    shadowml/WestBeagle-7B-gen2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
    * [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
    * [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)

    ## 🧩 Configuration

    ```yaml
    slices:
      - sources:
          - model: mlabonne/NeuralBeagle14-7B
            layer_range: [0, 32]
          - model: FelixChao/WestSeverus-7B-DPO-v2
            layer_range: [0, 32]
    merge_method: slerp
    base_model: mlabonne/NeuralBeagle14-7B
    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
    ```

    ## 💻 Usage

    ```python
    !pip install -qU transformers accelerate

    from transformers import AutoTokenizer
    import transformers
    import torch

    model = "shadowml/shadowml/WestBeagle-7B-gen2"
    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"])
    ```