@xenova/transformers - npm Package Compare versions

Comparing version 2.5.0 to 2.5.1

package.json

 {
   "name": "@xenova/transformers",
-  "version": "2.5.0",
+  "version": "2.5.1",
   "description": "State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!",
@@ -5,0 +5,0 @@ "main": "./src/transformers.js",

README.md

@@ -101,3 +101,3 @@
 <script type="module">
-    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.0';
+    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.1';
 </script>
@@ -116,2 +116,3 @@ ```
 | Code Playground   | In-browser code completion website | [link](./examples/code-completion/) |
+| Semantic Image Search | Search for images with text (Next.js + Supabase) | [link](./examples/semantic-image-search/) |
 | React             | Multilingual translation website | [link](./examples/react-translator/) |
@@ -129,3 +130,3 @@ | Browser extension | Text classification extension    | [link](./examples/extension/) |
 
-By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.0/dist/), which should work out-of-the-box. You can customize this as follows:
+By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.1/dist/), which should work out-of-the-box. You can customize this as follows:
 
@@ -263,2 +264,4 @@
 1. **[CodeGen](https://huggingface.co/docs/transformers/model_doc/codegen)** (from Salesforce) released with the paper [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong.
+1. **[DeBERTa](https://huggingface.co/docs/transformers/model_doc/deberta)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
+1. **[DeBERTa-v2](https://huggingface.co/docs/transformers/model_doc/deberta-v2)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
 1. **[DETR](https://huggingface.co/docs/transformers/model_doc/detr)** (from Facebook) released with the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko.
@@ -265,0 +268,0 @@ 1. **[DistilBERT](https://huggingface.co/docs/transformers/model_doc/distilbert)** (from HuggingFace), released together with the paper [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://arxiv.org/abs/1910.01108) by Victor Sanh, Lysandre Debut and Thomas Wolf. The same method has been applied to compress GPT2 into [DistilGPT2](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation), RoBERTa into [DistilRoBERTa](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation), Multilingual BERT into [DistilmBERT](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation) and a German version of DistilBERT.

src/env.js

@@ -32,3 +32,3 @@ /**
 
-const VERSION = '2.5.0';
+const VERSION = '2.5.1';
 
@@ -35,0 +35,0 @@ // Check if various APIs are available (depends on environment)

src/pipelines.js

@@ -463,4 +463,4 @@ /**
  * let text = 'I enjoy walking with my cute dog,';
- * let generator = await pipeline('text-generation', 'Xenova/distilgpt2');
- * let output = await generator(text);
+ * let classifier = await pipeline('text-generation', 'Xenova/distilgpt2');
+ * let output = await classifier(text);
  * console.log(output);
@@ -473,4 +473,4 @@ * // [{ generated_text: "I enjoy walking with my cute dog, and I love to play with the other dogs." }]
  * let text = 'Once upon a time, there was';
- * let generator = await pipeline('text-generation', 'Xenova/distilgpt2');
- * let output = await generator(text, {
+ * let classifier = await pipeline('text-generation', 'Xenova/distilgpt2');
+ * let output = await classifier(text, {
  *     temperature: 2,
@@ -494,4 +494,4 @@ *     max_new_tokens: 10,
  * let text = 'def fib(n):';
- * let generator = await pipeline('text-generation', 'Xenova/codegen-350M-mono');
- * let output = await generator(text, {
+ * let classifier = await pipeline('text-generation', 'Xenova/codegen-350M-mono');
+ * let output = await classifier(text, {
  *     max_new_tokens: 40,
@@ -556,2 +556,31 @@ * });
  * can be chosen at runtime. It usually means it's slower but it is **much** more flexible.
+ * 
+ * **Example:** Zero shot classification with `Xenova/mobilebert-uncased-mnli`.
+ * ```javascript
+ * let text = 'Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.';
+ * let labels = [ 'mobile', 'billing', 'website', 'account access' ];
+ * let classifier = await pipeline('zero-shot-classification', 'Xenova/mobilebert-uncased-mnli');
+ * let output = await classifier(text, labels);
+ * console.log(output);
+ * //  {
+ * //    sequence: 'Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.',
+ * //    labels: [ 'mobile', 'website', 'billing', 'account access' ],
+ * //    scores: [ 0.5562091040482018, 0.1843621307860853, 0.13942646639336376, 0.12000229877234923 ]
+ * //  }
+ * ```
+ * 
+ * **Example:** Zero shot classification with `Xenova/nli-deberta-v3-xsmall` (multi-label).
+ * ```javascript
+ * let text = 'I have a problem with my iphone that needs to be resolved asap!';
+ * let labels = [ 'urgent', 'not urgent', 'phone', 'tablet', 'computer' ];
+ * let classifier = await pipeline('zero-shot-classification', 'Xenova/nli-deberta-v3-xsmall');
+ * let output = await classifier(text, labels, { multi_label: true });
+ * console.log(output);
+ * // {
+ * //   sequence: 'I have a problem with my iphone that needs to be resolved asap!',
+ * //   labels: [ 'urgent', 'phone', 'computer', 'tablet', 'not urgent' ],
+ * //   scores: [ 0.9958870956360275, 0.9923963400697035, 0.002333537946160235, 0.0015134138567598765, 0.0010699384208377163 ]
+ * // }
+ * ```
+ * 
  * @extends Pipeline
@@ -583,3 +612,3 @@ */
 
-        this.contradiction_id = this.label2id['contradiction'];
+        this.contradiction_id = this.label2id['contradiction'] ?? this.label2id['not_entailment'];
         if (this.contradiction_id === undefined) {
@@ -586,0 +615,0 @@ console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id.");

src/utils/core.js

@@ -159,4 +159,4 @@
  * Adapted from https://stackoverflow.com/a/6768642/13989043
- * @param  {...any} arrs Arrays to merge.
- * @returns The merged array.
+ * @param  {Array[]} arrs Arrays to merge.
+ * @returns {Array} The merged array.
  */
@@ -163,0 +163,0 @@ export function mergeArrays(...arrs) {

types/env.d.ts

@@ -22,3 +22,3 @@ export namespace env {
 declare const __dirname: any;
-declare const VERSION: "2.5.0";
+declare const VERSION: "2.5.1";
 declare const localModelPath: any;
@@ -25,0 +25,0 @@ declare const FS_AVAILABLE: boolean;

types/pipelines.d.ts

@@ -162,4 +162,4 @@ /**
  * let text = 'I enjoy walking with my cute dog,';
- * let generator = await pipeline('text-generation', 'Xenova/distilgpt2');
- * let output = await generator(text);
+ * let classifier = await pipeline('text-generation', 'Xenova/distilgpt2');
+ * let output = await classifier(text);
  * console.log(output);
@@ -172,4 +172,4 @@ * // [{ generated_text: "I enjoy walking with my cute dog, and I love to play with the other dogs." }]
  * let text = 'Once upon a time, there was';
- * let generator = await pipeline('text-generation', 'Xenova/distilgpt2');
- * let output = await generator(text, {
+ * let classifier = await pipeline('text-generation', 'Xenova/distilgpt2');
+ * let output = await classifier(text, {
  *     temperature: 2,
@@ -193,4 +193,4 @@ *     max_new_tokens: 10,
  * let text = 'def fib(n):';
- * let generator = await pipeline('text-generation', 'Xenova/codegen-350M-mono');
- * let output = await generator(text, {
+ * let classifier = await pipeline('text-generation', 'Xenova/codegen-350M-mono');
+ * let output = await classifier(text, {
  *     max_new_tokens: 40,
@@ -223,2 +223,31 @@ * });
  * can be chosen at runtime. It usually means it's slower but it is **much** more flexible.
+ *
+ * **Example:** Zero shot classification with `Xenova/mobilebert-uncased-mnli`.
+ * ```javascript
+ * let text = 'Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.';
+ * let labels = [ 'mobile', 'billing', 'website', 'account access' ];
+ * let classifier = await pipeline('zero-shot-classification', 'Xenova/mobilebert-uncased-mnli');
+ * let output = await classifier(text, labels);
+ * console.log(output);
+ * //  {
+ * //    sequence: 'Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.',
+ * //    labels: [ 'mobile', 'website', 'billing', 'account access' ],
+ * //    scores: [ 0.5562091040482018, 0.1843621307860853, 0.13942646639336376, 0.12000229877234923 ]
+ * //  }
+ * ```
+ *
+ * **Example:** Zero shot classification with `Xenova/nli-deberta-v3-xsmall` (multi-label).
+ * ```javascript
+ * let text = 'I have a problem with my iphone that needs to be resolved asap!';
+ * let labels = [ 'urgent', 'not urgent', 'phone', 'tablet', 'computer' ];
+ * let classifier = await pipeline('zero-shot-classification', 'Xenova/nli-deberta-v3-xsmall');
+ * let output = await classifier(text, labels, { multi_label: true });
+ * console.log(output);
+ * // {
+ * //   sequence: 'I have a problem with my iphone that needs to be resolved asap!',
+ * //   labels: [ 'urgent', 'phone', 'computer', 'tablet', 'not urgent' ],
+ * //   scores: [ 0.9958870956360275, 0.9923963400697035, 0.002333537946160235, 0.0015134138567598765, 0.0010699384208377163 ]
+ * // }
+ * ```
+ *
  * @extends Pipeline
@@ -225,0 +254,0 @@ */

types/tokenizers.d.ts

@@ -40,12 +40,12 @@ declare const TokenizerModel_base: new () => {
      * @param {string[]} tokens The tokens to encode.
-     * @returns {number[]} The encoded token IDs.
+     * @returns {string[]} The encoded token IDs.
      */
-    _call(tokens: string[]): number[];
+    _call(tokens: string[]): string[];
     /**
      * Encodes a list of tokens into a list of token IDs.
      * @param {string[]} tokens The tokens to encode.
-     * @returns {number[]} The encoded token IDs.
+     * @returns {string[]} The encoded tokens.
      * @throws Will throw an error if not implemented in a subclass.
      */
-    encode(tokens: string[]): number[];
+    encode(tokens: string[]): string[];
     /**
@@ -207,2 +207,6 @@ * Converts a list of tokens into a list of token IDs.
 }
+export class DebertaTokenizer extends PreTrainedTokenizer {
+}
+export class DebertaV2Tokenizer extends PreTrainedTokenizer {
+}
 export class DistilBertTokenizer extends PreTrainedTokenizer {
@@ -391,2 +395,4 @@ }
         DistilBertTokenizer: typeof DistilBertTokenizer;
+        DebertaTokenizer: typeof DebertaTokenizer;
+        DebertaV2Tokenizer: typeof DebertaV2Tokenizer;
         BertTokenizer: typeof BertTokenizer;
@@ -430,2 +436,24 @@ MobileBertTokenizer: typeof MobileBertTokenizer;
 export type PretrainedOptions = import('./utils/hub.js').PretrainedOptions;
+export type BPENode = {
+    /**
+     * The token associated with the node
+     */
+    token: string;
+    /**
+     * A positional bias for the node.
+     */
+    bias: number;
+    /**
+     * The score of the node.
+     */
+    score?: number;
+    /**
+     * The previous node in the linked list.
+     */
+    prev?: BPENode;
+    /**
+     * The next node in the linked list.
+     */
+    next?: BPENode;
+};
 export type SplitDelimiterBehavior = 'removed' | 'isolated' | 'mergedWithPrevious' | 'mergedWithNext' | 'contiguous';
@@ -432,0 +460,0 @@ declare const Normalizer_base: new () => {

types/utils/core.d.ts

@@ -78,6 +78,6 @@ /**
  * Adapted from https://stackoverflow.com/a/6768642/13989043
- * @param  {...any} arrs Arrays to merge.
- * @returns The merged array.
+ * @param  {Array[]} arrs Arrays to merge.
+ * @returns {Array} The merged array.
  */
-export function mergeArrays(...arrs: any[]): any;
+export function mergeArrays(...arrs: any[][]): any[];
 /**
@@ -84,0 +84,0 @@ * A base class for creating callable objects.

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Improved metrics

Total package byte prevSize

44483526

increased by0.31%

Number of package files

59

increased by5.36%

Lines of code

38030

increased by4.39%

Number of lines in readme file

285

increased by1.06%

No dependency changes