--- tags: - merge - mergekit - lazymergekit - KoboldAI/LLaMA2-13B-Tiefighter - abacusai/Giraffe-13b-32k-v3 base_model: - KoboldAI/LLaMA2-13B-Tiefighter - abacusai/Giraffe-13b-32k-v3 --- INTERM STEP VERSION: Step 1 in trying to make Tiefighter 32,768 context. This version is not usable in current form. Step 2 however (a linear remerge of Tiefighter with this merge) is however working. GGUFs are also working... at 32768 context. Step 2 is here: [DavidAU/D_AU-Tiefighter-Plus-Giraffe-13B-32k-slerp](DavidAU/D_AU-Tiefighter-Plus-Giraffe-13B-32k-slerp) # D_AU-Tiefighter-Giraffe-13B-32k-slerp D_AU-Tiefighter-Giraffe-13B-32k-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [KoboldAI/LLaMA2-13B-Tiefighter](https://huggingface.co/KoboldAI/LLaMA2-13B-Tiefighter) * [abacusai/Giraffe-13b-32k-v3](https://huggingface.co/abacusai/Giraffe-13b-32k-v3) ## 🧩 Configuration ```yaml slices: - sources: - model: KoboldAI/LLaMA2-13B-Tiefighter layer_range: [0, 40] - model: abacusai/Giraffe-13b-32k-v3 layer_range: [0, 40] merge_method: slerp base_model: abacusai/Giraffe-13b-32k-v3 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 = "DavidAU/D_AU-Tiefighter-Giraffe-13B-32k-slerp" 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"]) ```