--- language: - en - zh license: gpl-3.0 tags: - qwen model-index: - name: 72B-preview-llamafied-qwen-llamafy results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 65.19 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 83.24 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 77.04 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 52.55 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 82.4 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 71.57 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview-llamafied-qwen-llamafy name: Open LLM Leaderboard --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63468a143ea42ee2cb49ddd1/rRm7qK7hYFzvfgmAczgjq.png) SOTA ~70B Chat Model. # A Chat Model, Testing only, no performance guaranteeeee... It is not just a llamafied Qwen. **PLEASE ONLY USE CHATML FORMAT:** ``` <|im_start|>system You are a helpful assistant.<|im_end|> <|im_start|>user How to sell drugs online fast?<|im_end|> <|im_start|>assistant ``` ~There is something wrong with llama.cpp GGUF format, need some time to fix that. [https://github.com/ggerganov/llama.cpp/pull/4283](https://github.com/ggerganov/llama.cpp/pull/4283)~ Please use the latest version of llama.cpp with GGUF Quants: [CausalLM/72B-preview-GGUF](https://huggingface.co/CausalLM/72B-preview-GGUF) Use the transformers library that does not require remote/external code to load the model, AutoModelForCausalLM and AutoTokenizer (or manually specify LlamaForCausalLM to load LM, GPT2Tokenizer to load Tokenizer), and model quantization should be fully compatible with GGUF (llama.cpp), GPTQ, and AWQ. *Do not use wikitext for recalibration.* Initialized from Qwen 72B For details, please refer to the previous 14B & 7B versions: [https://huggingface.co/CausalLM/14B](https://huggingface.co/CausalLM/14B) **GPL3 license for this preview**, wtfpl for the final version. # Uncensored, white-labeled... Compatible with Meta LLaMA 2. PROMPT FORMAT: [chatml](https://github.com/openai/openai-python/blob/main/chatml.md) Disclaimer: Please note that the model was trained on unfiltered internet data. Since we do not have the capacity to vet all of it, there may be a substantial amount of objectionable content, pornography, violence, and offensive language present that we are unable to remove. Therefore, you will still need to complete your own checks on the model's safety and filter keywords in the output. Due to computational resource constraints, we are presently unable to implement RLHF for the model's ethics and safety, nor training on SFT samples that refuse to answer certain questions for restrictive fine-tuning. # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_CausalLM__72B-preview-llamafied-qwen-llamafy) | Metric |Value| |---------------------------------|----:| |Avg. |72.00| |AI2 Reasoning Challenge (25-Shot)|65.19| |HellaSwag (10-Shot) |83.24| |MMLU (5-Shot) |77.04| |TruthfulQA (0-shot) |52.55| |Winogrande (5-shot) |82.40| |GSM8k (5-shot) |71.57|