--- license: other tags: - merge - mergekit - lazymergekit base_model: - nbeerbower/llama-3-stella-8B - Hastagaras/llama-3-8b-okay - nbeerbower/llama-3-gutenberg-8B - openchat/openchat-3.6-8b-20240522 - Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 - cstr/llama3-8b-spaetzle-v20 - mlabonne/ChimeraLlama-3-8B-v3 - flammenai/Mahou-1.1-llama3-8B - KingNish/KingNish-Llama3-8b --- # Daredevil-8B **tl;dr: It looks like a successful merge** Daredevil-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B) * [Hastagaras/llama-3-8b-okay](https://huggingface.co/Hastagaras/llama-3-8b-okay) * [nbeerbower/llama-3-gutenberg-8B](https://huggingface.co/nbeerbower/llama-3-gutenberg-8B) * [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522) * [Kukedlc/NeuralLLaMa-3-8b-DT-v0.1](https://huggingface.co/Kukedlc/NeuralLLaMa-3-8b-DT-v0.1) * [cstr/llama3-8b-spaetzle-v20](https://huggingface.co/cstr/llama3-8b-spaetzle-v20) * [mlabonne/ChimeraLlama-3-8B-v3](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v3) * [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B) * [KingNish/KingNish-Llama3-8b](https://huggingface.co/KingNish/KingNish-Llama3-8b) ## 🔎 Applications It is a highly functional censored model. You might want to add `` as an additional stop string. ## ⚡ Quantization * **GGUF**: https://huggingface.co/mlabonne/Daredevil-8B-GGUF ## 🏆 Evaluation | Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: | | [**mlabonne/Daredevil-8B**](https://huggingface.co/mlabonne/Daredevil-8B) [📄](https://gist.github.com/mlabonne/080f9c5f153ea57a7ab7d932cf896f21) | **55.87** | **44.13** | **73.52** | **59.05** | **46.77** | | [mlabonne/ChimeraLlama-3-8B](https://huggingface.co/mlabonne/Chimera-8B) [📄](https://gist.github.com/mlabonne/28d31153628dccf781b74f8071c7c7e4) | 51.58 | 39.12 | 71.81 | 52.4 | 42.98 | | [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) | 51.34 | 41.22 | 69.86 | 51.65 | 42.64 | | [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 | ## 🌳 Model family tree ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/LplqNg6iXHm_JXfX02Aj1.png) ## 🧩 Configuration ```yaml models: - model: NousResearch/Meta-Llama-3-8B # No parameters necessary for base model - model: nbeerbower/llama-3-stella-8B parameters: density: 0.6 weight: 0.16 - model: Hastagaras/llama-3-8b-okay parameters: density: 0.56 weight: 0.1 - model: nbeerbower/llama-3-gutenberg-8B parameters: density: 0.6 weight: 0.18 - model: openchat/openchat-3.6-8b-20240522 parameters: density: 0.56 weight: 0.12 - model: Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 parameters: density: 0.58 weight: 0.18 - model: cstr/llama3-8b-spaetzle-v20 parameters: density: 0.56 weight: 0.08 - model: mlabonne/ChimeraLlama-3-8B-v3 parameters: density: 0.56 weight: 0.08 - model: flammenai/Mahou-1.1-llama3-8B parameters: density: 0.55 weight: 0.05 - model: KingNish/KingNish-Llama3-8b parameters: density: 0.55 weight: 0.05 merge_method: dare_ties base_model: NousResearch/Meta-Llama-3-8B dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "mlabonne/Daredevil-8B" 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"]) ```