("mistral-nemo")model=Transformer.from_folder(os.environ.get("NEMO_MODEL"))completion_request=ChatCompletionRequest(tools=[Tool(function=Function(name="get_current_weather",description="Get the current weather",parameters={"type":"object","properties": {"location": {"type":"string","description...
Mistral-Nemo-Instruct-2407Mistral-Nemo-Instruct-2407 是 Mistral AI 和 NVIDIA 联合开源的 Mistral-Nemo-Base-2407 指令微调版本,其性能明显优于现有较小或类似尺寸的模型。Mistral NeMo 参数量为 120 亿(12B),上下文窗口为 128k,其推理、世界知识和编码准确性在同类规模中处于领先地位。由于 Mistral NeMo 依赖于...
Use --model_type mistral-nemo-base-2407 and --model_type mistral-nemo-instruct-2407 to begin. 2024.07.19: Support Q-Galore, this algorithm can reduce the training memory cost by 60% (qwen-7b-chat, full, 80G -> 35G), use swift sft --model_type xxx --use_galore true --galore_...
模型输出：The image portrays a serene autumn scene in what appears to be a traditional Chineseland...
Nemotron-4 15B 是一个规模庞大、多语言能力出色、参数达到150亿的大型语言模型。它通过在8万亿个文本标记上进行训练,实现了极高的多语言性能。102 在广泛的英语任务、多语言任务和编码任务上,Nemotron-4 15B 都表现出色,在与其他同样规模的开放模型进行比较时,在4个下游评估领域中性能较好,与领先的开放模型在其他...
Use --model_type mistral-nemo-base-2407 and --model_type mistral-nemo-instruct-2407 to begin. 2024.07.19: Support Q-Galore, this algorithm can reduce the training memory cost by 60% (qwen-7b-chat, full, 80G -> 35G), use swift sft --model_type xxx --use_galore true --galore_...
Chinese 59.0% Japanese 59.0% Usage The model can be used with three different frameworks mistral_inference: See here transformers: See here NeMo: See nvidia/Mistral-NeMo-12B-Instruct Mistral Inference Install It is recommended to use mistralai/Mistral-Nemo-Instruct-2407 with mistral-inference. For...