Mar 11, 2024 · This is a question on the Huggingface transformers library. This class cannot be instantiated directly using __init__() (throws an error). pickle) or as raw text device_map="auto" automatically allocates the model weights to your fastest device first. AutoTokenizer ¶ class transformers. from_pretrained 方法加载 tokenizer。 Contribute to QwenLM/Qwen3-Embedding development by creating an account on GitHub. from We’re on a journey to advance and democratize artificial intelligence through open source and open science. from_pretrained() tokenizer. AutoTokenizer ¶ class transformers. This tokenizer is taking incredibly long Jun 20, 2023 · tokenizer = AutoTokenizer. encode () and in particular, tokenizer. float32 by default). Is there a way to automatically infer the device of the model when using auto device map, and cast the input tensor to that? Here’s what I have now: import transformers import torch DEVICE = "cuda" if torch. from_pretrained ('local/path') doesn't? Oct 5, 2023 · I want to load a huggingface pretrained transformer model directly to GPU (not enough CPU space) e. cuda. Could you print the hf_device_map attribute of the model and try to move the inputs to cuda device 0 and 1? May 22, 2020 · Do you mean AutoTokenizer. Below is a demo usage for a quick start: from transformers import AutoModelForCausalLM, AutoTokenizer device = "cuda" # the device to load the model onto model = AutoModelForCausalLM. to (device) outputs = model (**inputs) Feb 23, 2022 · I'm using an tweaked version of the uer/roberta-base-chinese-extractive-qa model. PyTorch's `AutoTokenizer` is a powerful tool that simplifies the tokenization process, offering a unified interface to work with different pre-trained tokenizers from the Hugging Face Transformers library. from_pretrained(model_name, fast=True) Now, when I try to move the model back to CPU to free up GPU memory for other processing, I get an error: Nov 6, 2024 · Learn how to fine-tune a natural language processing model with Hugging Face Transformers on a single node GPU. is_available() else "cpu" tokenizer = transformers. Nov 14, 2025 · In the field of natural language processing (NLP), tokenization is a fundamental step that breaks text into smaller units called tokens. Apr 1, 2021 · 文章浏览阅读1. I've followed this tutorial (colab notebook) in order to finetune my model. e. encode() and in particular, tokenizer. Setting this to -1 will leverage CPU, >=0 will run the model on the associated CUDA device id. Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud. import ctranslate2 import transformers generator = ctranslate2. We’re on a journey to advance and democratize artificial intelligence through open source and open science. 1 day ago · Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills Sep 14, 2024 · I have a model that I was reading from huggingface using the following code: from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer. is_available() else "mps" if torch. loading BERT from transformers import AutoModelForCausalLM model = AutoModelForCausalLM. device (int, optional, defaults to -1) – Device ordinal for CPU/GPU supports. 1k次，点赞20次，收藏21次。⚠️ 如果你添加了新词，记得也要更新模型的 embedding 层！训练自己的 BPE Tokenizer# 初始化 BPE 模型# 定义特殊 token# 训练器配置# 读取训练数据（假设是 JSONL 文件）# 训练 tokenizer# 保存 tokenizer。_autotokenizer The AutoTokenizer class in the Hugging Face transformers library is a versatile tool designed to handle tokenization tasks for a wide range of pre-trained models. Sep 8, 2025 · 文章浏览阅读8. Sep 14, 2024 · I have a model that I was reading from huggingface using the following code: from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer. Oct 8, 2024 · AutoTokenizer. pretrained_model_name_or_path 类型: str 描述: 预训练模型名称或模型目录路径。 We’re on a journey to advance and democratize artificial intelligence through open source and open science. Complete guide with code examples, best practices, and performance tips. backends. Generator("falcon-7b-instruct", device="cuda") tokenizer = transformers. AutoTokenizer. from_pretrained ("THUDM/glm-4v-9b", trust_remote_code=True) We’re on a journey to advance and democratize artificial intelligence through open source and open science. 8k次，点赞62次，收藏65次。本文对使用transformers的AutoTokenizer进行介绍，他最大的特点是允许开发者通过一个统一的接口来加载任何预训练模型对应的分词器（tokenizer），而无需直接指定分词器的精确类型。这意味着，当知道模型的名称时，可以使用AutoTokenizer自动获取与该模型匹配的 Sep 29, 2025 · We’re on a journey to advance and democratize artificial intelligence through open source and open science. device_map (str or dict[str, Union[int, str, torch. Mar 23, 2022 · 🚀 Feature request I think it will make sense if the tokenizer. AutoTokenizer [source] ¶ AutoTokenizer is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when created with the AutoTokenizer. to (device) model = model. encode_plus () accepting a string as input, will also get "device" as an argument and cast the resulting tensors to the given device. We would like to show you a description here but the site won’t allow us. from_pretrained 是 Hugging Face transformers 库中用于加载预训练 分词器 的常用方法之一。 它支持多个参数，使得分词器加载过程具有灵活性，可以根据需要自定义加载方式。 1. This blog post aims to provide an in-depth We’re on a journey to advance and democratize artificial intelligence through open source and open science. nn. device], optional) — Sent directly as model_kwargs (just a simpler shortcut). Tensor of shape (batch_size, sequence_length), optional) — Mask to avoid performing attention on padding token indices. Otherwise, in case of encode_plus (), one has to loop through the output dict and manually cast the created tensors. attention_mask (torch. from_pretrained("tiiuae/falcon-7b-instruct") prompt = ( "Girafatron is obsessed with giraffes, the most glorious animal on the face of this Earth. from_pretrained() class method. . 3 billion parameter open-source language model. Dec 22, 2022 · AutoTokenizer是Huggingface提供的“AutoClass”系列的高级对象，可以便捷的调用tokenizers库（Huggingface提供的专门用于分词等操作的代码库）实现加载预训练的分词器。 device = "cuda:0" if torch. from_pretrained( model_id, torch_dtype=torch. json 中定义的分词器类型自动检测分词器类型。 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production - huggingface/tokenizers We’re on a journey to advance and democratize artificial intelligence through open source and open science. from_pretrained ('bert-large-uncased') inputs = tokenizer (sentence, return_tensors="pt"). Aug 1, 2024 · The tutorial covers accessing, quantizing, fine-tuning, merging, and saving this powerful 7. DataParallel(model, device_ids=[0,1]) The Huggingface docs on training with multiple GPUs are not really clear to me and don't have an example of using the Trainer. encode () and PreTrainedTokenizer. import torch from PIL import Image from transformers import AutoModelForCausalLM, AutoTokenizer device = "cuda" tokenizer = AutoTokenizer. Jul 15, 2025 · 文章浏览阅读3. from_pretrained ('bert-large-uncased') model = BertModel. mps. is_available () else "cpu" sentence = 'Hello World!' tokenizer = AutoTokenizer. I've implemented the distilbert model and distilberttokenizer. When accelerate library is present, set device_map="auto" to compute the most optimized device_map automatically (see here for more information). from_pretrained ('bert-base-uncased') works but AutoTokenizer. Since my model uses additional tokens, I added them to the Dec 3, 2023 · NLPだったり機械学習を触ったことがある人ならなんとなーくわかるだろうけどぶっちゃけ詳しくわかってない人も多いと思うので、備忘録も兼ねてよく使う関数の動作やパラメータについて解説していこうと思います。 以下はLLMをとりあえず使ってみようでよく見かけるコードです。 コードは We’re on a journey to advance and democratize artificial intelligence through open source and open science. from_pretrained (pretrained_model_name_or_path) class method. from_pretrained ('local/path') doesn't? 近两年大模型火出天际；同时，也诞生了大量针对大模型的优化技术。本系列将针对一些常见大模型优化技术进行讲解。 大模型推理优化技术-KV Cache大模型推理服务调度优化技术-Continuous batching大模型底显存推理优… We’re on a journey to advance and democratize artificial intelligence through open source and open science. AutoTokenizer [source] ¶ This is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when created with the AutoTokenizer. GITHUB HUGGING FACE MODELSCOPE API Quick Start It is simple to use Qwen through Hugging Face Transformers. May 22, 2020 · Do you mean AutoTokenizer. g. Trying to load my locally saved model model = AutoModelForCausalLM. Jun 19, 2024 · Let’s learn about AutoTokenizer in the Huggingface Transformers library. - QwenLM/Qwen3 Dec 26, 2022 · You did move the inputs when processing on one of the two GPUs, it might be necessary here too. from_pretrained(model_path) mode Links In the following, we provide important links for you to refer to our opensource resources. call () for details. Instantiate one of the configuration classes of the library from a pretrained model configuration. See PreTrainedTokenizer. The configuration class to instantiate is selected based on the model_type property of the config object that is loaded, or when it’s missing, by falling back to using pattern matching on pretrained_model_name_or_path: aimv2 — Aimv2Config (AIMv2 model) aimv2_vision_model — Aimv2VisionConfig Feb 15, 2023 · I have access to six 24GB GPUs. from AutoTokenizer ¶ class transformers. Mar 23, 2022 · I think it will make sense if the tokenizer. When I try to load some HuggingFace models, for example the following from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer. We’ll break it down step by step to make it easy to understand, starting with why we need tokenizers in the first place. AutoTokenizer ¶ class transformers. from_pretrained ("THUDM/glm-4v-9b", trust_remote_code=True) Auto Classes in Hugging Face simplify the process of retrieving relevant models, configurations, and tokenizers for pre-trained architectures using their names or paths. How should I configure device_map (or other parameters) so that the model runs on both GPUs? Jun 11, 2025 · Learn AutoTokenizer for effortless text preprocessing in NLP. 9w次，点赞23次，收藏58次。本文介绍如何使用Tokenizer对文本进行预处理，包括将文本分割成tokens并转换为数字，以及如何处理批量文本输入。同时，文章还讲解了如何利用Tokenizer与模型进行交互，包括模型的保存与加载。 Oct 2, 2019 · Indices can be obtained using AutoTokenizer. from_pretrained(model_path) mode Contribute to saivamshinamala/raft_interns development by creating an account on GitHub. bfloat16, device_map="cuda:3", ) There are many GPUs on the server, but I can only use two of them. While I know how to train using multiple GPUs, it is not clear how to use multiple GPUs when coming to this stage. Mask values selected in [0, 1]: 1 for tokens that are not masked,. binary_output (bool, optional, defaults to False) – Flag indicating if the output the pipeline should happen in a binary format (i. from_pretrained can not determine which tokenizer type to instantiate itself? Why AutoTokenizer. May 29, 2024 · I have pre-trained a "meta-llama/Llama-2-7b-chat-hf" model using the transformers library. from_pretrained("finetuned_model") yields K Mar 22, 2023 · model = torch. Aug 9, 2024 · from transformers import AutoTokenizer, AutoModelForCausalLM model = AutoModelForCausalLM. encode_plus() accepting a string as input, will also get "device" as an argument and cast the res We’re on a journey to advance and democratize artificial intelligence through open source and open science. dtype="auto" directly initializes the model weights in the data type they're stored in, which can help avoid loading the weights twice (PyTorch loads weights in torch. 分词器用于为模型准备文本输入。 示例: 创建一个 AutoTokenizer 并用它来对一个句子进行分词。 这将根据 tokenizer. Mar 26, 2024 · 如何自动加载 tokenizer 前面介绍了如何从 from transformers import AutoTokenizer 导入 AutoTokenizer，接下来介绍使用 AutoTokenizer. AutoTokenizer [source] ¶ AutoTokenizer is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when created with the AutoTokenizer. Feb 8, 2021 · I'm dealing with a huge text dataset for content classification.

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