--- language: - en license: llama3 library_name: transformers pipeline_tag: text2text-generation model-index: - name: Al_Dente_v1_8b 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: 36.94 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b 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: 27.25 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b 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: 3.02 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b 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: 6.6 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b 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: 8.27 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b 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: 20.67 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b name: Open LLM Leaderboard --- **Model Name: Llama 3 Al_Dente_v1_8b** # Llama 3 Al_Dente_v1_8b is trained on various SFT Datasets
Passionate about Generative AI? I help companies to privately train and deploy custom LLM/MLLM affordably. For startups, I can even assist with securing GPU grants to get you started. Let's chat! https://www.linkedin.com/in/pankajam Looking forward to connecting!
### NOTICE By providing proper credit and attribution, you are granted permission to use this model as a foundational base for further Full fine tuning, DPO, PPO or ORPO tuning and any kind of Merges. I actively encourage users to customize and enhance the model according to their specific needs, as this version is designed to be a comprehensive general model. Dive in and innovate! ### Evaluation Coming Soon.. ### Example Usage Here is the ChatML prompt format ``` <|im_start|>system You are Al Dente, a helpful AI assistant.<|im_end|> <|im_start|>user Hello Al Dente, what can you do for me?<|im_end|> <|im_start|>assistant ``` Below shows a code example on how to use this model ```python from transformers import AutoModel, AutoTokenizer model_slug = "pankajmathur/Al_Dente_v1_8b" model = AutoModel.from_pretrained(model_slug) tokenizer = AutoTokenizer.from_pretrained(model_slug) messages = [ {"role": "system", "content": "You are Al Dente, a helpful AI assistant."}, {"role": "user", "content": "Hello Al Dente, what can you do for me?"} ] gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt") model.generate(**gen_input) ``` This model is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE) **Quants** GGUF : Coming Soon AWQ: Coming Soon # [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_pankajmathur__Al_Dente_v1_8b) | Metric |Value| |-------------------|----:| |Avg. |17.12| |IFEval (0-Shot) |36.94| |BBH (3-Shot) |27.25| |MATH Lvl 5 (4-Shot)| 3.02| |GPQA (0-shot) | 6.60| |MuSR (0-shot) | 8.27| |MMLU-PRO (5-shot) |20.67|