HuggingFace镜像/Janus-1.3B-ONNX
模型介绍文件和版本分析
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https://huggingface.co/deepseek-ai/Janus-1.3B 包含 ONNX 权重，以确保与 Transformers.js 兼容。

使用方法（Transformers.js）

如果您尚未安装，可以通过以下命令从 NPM 安装 Transformers.js JavaScript 库：

npm i @huggingface/transformers

示例： 图像+文本到文本

import { AutoProcessor, MultiModalityCausalLM } from "@huggingface/transformers";

// Load processor and model
const model_id = "onnx-community/Janus-1.3B-ONNX";
const processor = await AutoProcessor.from_pretrained(model_id);
const model = await MultiModalityCausalLM.from_pretrained(model_id);

// Prepare inputs
const conversation = [
  {
    role: "User",
    content: "<image_placeholder>\nConvert the formula into latex code.",
    images: ["https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/quadratic_formula.png"],
  },
];
const inputs = await processor(conversation);

// Generate response
const outputs = await model.generate({
  ...inputs,
  max_new_tokens: 150,
  do_sample: false,
});

// Decode output
const new_tokens = outputs.slice(null, [inputs.input_ids.dims.at(-1), null]);
const decoded = processor.batch_decode(new_tokens, { skip_special_tokens: true });
console.log(decoded[0]);

示例输出：

Sure, here is the LaTeX code for the given formula:

```
x = \frac{-b \pm \sqrt{b^2 - 4a c}}{2a}
```

This code represents the mathematical expression for the variable $ x $.

示例： 文本转图像

import { AutoProcessor, MultiModalityCausalLM } from "@huggingface/transformers";

// Load processor and model
const model_id = "onnx-community/Janus-1.3B-ONNX";
const processor = await AutoProcessor.from_pretrained(model_id);
const model = await MultiModalityCausalLM.from_pretrained(model_id);

// Prepare inputs
const conversation = [
  {
    role: "User",
    content: "A cute and adorable baby fox with big brown eyes, autumn leaves in the background enchanting,immortal,fluffy, shiny mane,Petals,fairyism,unreal engine 5 and Octane Render,highly detailed, photorealistic, cinematic, natural colors.",
  },
];
const inputs = await processor(conversation, { chat_template: "text_to_image" });

// Generate response
const num_image_tokens = processor.num_image_tokens;
const outputs = await model.generate_images({
  ...inputs,
  min_new_tokens: num_image_tokens,
  max_new_tokens: num_image_tokens,
  do_sample: true,
});

// Save the generated image
await outputs[0].save("test.png");

示例输出：

image/pngimage/pngimage/pngimage/png
image/pngimage/pngimage/pngimage/png

想要试用该模型吗？可以查看在线WebGPU演示。