supports English text generation tasks with natural coding capabilities. Mixtral 8x7B is a popular, high-quality, sparse Mixture-of-Experts (MoE) model, that is ideal for text summarization, question
fromtransformersimportAutoModelForSequenceClassification,Trainer,TrainingArgumentsmodel=AutoModelForSequenceClassification.from_pretrained("mistral-7b",num_labels=2)training_args=TrainingArguments(output_dir='./results',num_train_epochs=3,per_device_train_batch_size=8)# 假设 `train_dataset` 和 `eval_datas...
The generative AI — large language model (LLM) developers market offers foundation models and APIs that enable enterprises to build natural language processing applications for a number of functions. These include content creation, summarization, classification, chat, sentiment analysis, and more. Enterp...
such as text summarization, classification, text completion, and code completion. To demonstrate the easy customizability of the model, Mistral AI has also released a Mistral 7B Instruct model for chat use cases, fine-tuned using a
Model Evaluation: Uses EvalScope as the evaluation backend and supports evaluation on 100+ datasets for both pure text and multi-modal models. Model Quantization: Supports AWQ, GPTQ, and BNB quantized exports, with models that can use vLLM/LmDeploy for inference acceleration and continue training...
SeqGPT Tongyi Lab self-developed text understanding model for information extraction and text classification Chinese 560M semantic understanding model SUS Southern University of Science and Technology model fine-tuned on YI ChineseEnglish 34B chat model Tongyi-Finance Tongyi finance series models ChineseEngl...
fromtransformersimportAutoModelForSequenceClassificationimporttorchmistral_model=AutoModelForSequenceClassification.from_pretrained(pretrained_model_name_or_path=mistral_checkpoint,num_labels=2,device_map="auto") 设置填充词元 id,因为 Mistral 7B 没有默认填充词元。
LoRA 旨在显著减少可训参数量，同时保持强大的下游任务性能。本文的主要目标是通过对 Hugging Face 的三个预训练模型进行 LoRA 微调，使之适用于序列分类任务。这三个预训练模型分别是: meta-llama/Llama-2-7b-hf、mistralai/Mistral-7B-v0.1 及 roberta-large。使用的硬件节点数: 1每个节点的 GPU 数: 1GPU ...
The Azure AI model inference API supportsAzure AI content safety. When you use deployments with Azure AI content safety turned on, inputs and outputs pass through an ensemble of classification models aimed at detecting and preventing the output of harmful content. The content filtering system detect...
performance benchmarks, indicating that is the superior model. But Large is cheaper to run than GPT-4. Given Large lost to GPT-4 on those performance benchmarks by only a few percentage points, it could be a suitable choice for organizations looking for a high-performing LLM at a lower ...