--- license: apache-2.0 tags: - Safetensors - mistral - text-generation-inference - merge - mistral - 7b - mistralai/Mistral-7B-Instruct-v0.1 - openaccess-ai-collective/jackalope-7b - transformers - pytorch - mistral - text-generation - en - dataset:Open-Orca/OpenOrca - dataset:LDJnr/LessWrong-Amplify-Instruct - dataset:LDJnr/Pure-Dove - dataset:LDJnr/Verified-Camel - dataset:PygmalionAI/PIPPA - dataset:meta-math/MetaMathQA - dataset:riddle_sense - arxiv:2306.02707 - arxiv:2301.13688 - license:apache-2.0 - autotrain_compatible - endpoints_compatible - has_space - text-generation-inference - region:us --- # jackalope-7b-Mistral-7B-Instruct-v0.1 jackalope-7b-Mistral-7B-Instruct-v0.1 is a merge of the following models: * [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) * [openaccess-ai-collective/jackalope-7b](https://huggingface.co/openaccess-ai-collective/jackalope-7b) ## 🧩 Configuration ```yaml slices: - sources: - model: mistralai/Mistral-7B-Instruct-v0.1 layer_range: [0, 32] - model: openaccess-ai-collective/jackalope-7b layer_range: [0, 32] merge_method: slerp base_model: mistralai/Mistral-7B-Instruct-v0.1 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 = "MaziyarPanahi/jackalope-7b-Mistral-7B-Instruct-v0.1" 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"]) ```