--- license: other tags: - merge - mergekit - lazymergekit - mlabonne/ChimeraLlama-3-8B-v2 - nbeerbower/llama-3-stella-8B - uygarkurt/llama-3-merged-linear base_model: - mlabonne/ChimeraLlama-3-8B-v2 - nbeerbower/llama-3-stella-8B - uygarkurt/llama-3-merged-linear model-index: - name: NeuralLLaMa-3-8b-DT-v0.1 results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 43.71 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 28.01 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 7.25 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 7.05 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 9.69 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 31.02 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Kukedlc/NeuralLLaMa-3-8b-DT-v0.1 name: Open LLM Leaderboard --- # NeuralLLaMa-3-8b-DT-v0.1 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/tK72e9RGnYyBVRy0T_Kba.png) NeuralLLaMa-3-8b-DT-v0.1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [mlabonne/ChimeraLlama-3-8B-v2](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v2) * [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B) * [uygarkurt/llama-3-merged-linear](https://huggingface.co/uygarkurt/llama-3-merged-linear) ## 🧩 Configuration ```yaml models: - model: NousResearch/Meta-Llama-3-8B # No parameters necessary for base model - model: mlabonne/ChimeraLlama-3-8B-v2 parameters: density: 0.33 weight: 0.2 - model: nbeerbower/llama-3-stella-8B parameters: density: 0.44 weight: 0.4 - model: uygarkurt/llama-3-merged-linear parameters: density: 0.55 weight: 0.4 merge_method: dare_ties base_model: NousResearch/Meta-Llama-3-8B parameters: int8_mask: true dtype: float16 ``` ## 🗨️ Chats ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/Uk89jeeRZ3Zh3wNBm6dXk.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/feYEkbM_TqeahAMOoiGoG.png) ## 💻 Usage ```python !pip install -qU transformers accelerate bitsandbytes from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, BitsAndBytesConfig import torch bnb_config = BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_use_double_quant=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16 ) MODEL_NAME = 'Kukedlc/NeuralLLaMa-3-8b-DT-v0.1' tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map='cuda:0', quantization_config=bnb_config) prompt_system = "You are an advanced language model that speaks Spanish fluently, clearly, and precisely.\ You are called Roberto the Robot and you are an aspiring post-modern artist." prompt = "Create a piece of art that represents how you see yourself, Roberto, as an advanced LLm, with ASCII art, mixing diagrams, engineering and let yourself go." chat = [ {"role": "system", "content": f"{prompt_system}"}, {"role": "user", "content": f"{prompt}"}, ] chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True) inputs = tokenizer(chat, return_tensors="pt").to('cuda') streamer = TextStreamer(tokenizer) stop_token = "<|eot_id|>" stop = tokenizer.encode(stop_token)[0] _ = model.generate(**inputs, streamer=streamer, max_new_tokens=1024, do_sample=True, temperature=0.7, repetition_penalty=1.2, top_p=0.9, eos_token_id=stop) ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Kukedlc__NeuralLLaMa-3-8b-DT-v0.1) | Metric |Value| |-------------------|----:| |Avg. |21.12| |IFEval (0-Shot) |43.71| |BBH (3-Shot) |28.01| |MATH Lvl 5 (4-Shot)| 7.25| |GPQA (0-shot) | 7.05| |MuSR (0-shot) | 9.69| |MMLU-PRO (5-shot) |31.02|