semantic-chunking - npm Package Compare versions

Comparing version 2.2.4 to 2.3.0

CHANGELOG.md

@@ -5,9 +5,19 @@ # Changelog
 
+## [2.3.0] - 2024-11-11
+### Updated
+- Updated `transformers.js` from v2 to v3
+- Migrated quantization option from `onnxEmbeddingModelQuantized` (boolean) to `dtype` ('p32', 'p16', 'q8', 'q4')
+- Updated Web UI to use new `dtype` option
+
+## [2.2.5] - 2024-11-08
+### Updated
+- Updated Web UI styles for smaller screens
+
 ## [2.2.4] - 2024-11-08
 ### Fixed
-- Fixed issue with Web UI embedding cache not being cleared when a new model is initialized.
+- Fixed issue with Web UI embedding cache not being cleared when a new model is initialized
 
 ## [2.2.3] - 2024-11-07
 ### Added
-- Web UI adjustments for display of truncated JSON results on screen but still allowing download of full results.
+- Web UI adjustments for display of truncated JSON results on screen but still allowing download of full results
 
@@ -14,0 +24,0 @@ ## [2.2.2] - 2024-11-07

chunkit.js

@@ -11,3 +11,2 @@ // ===========================
 
-import { env } from '@xenova/transformers';
 import { splitBySentence } from "string-segmenter"
@@ -34,3 +33,4 @@ import { DEFAULT_CONFIG } from './config.js';
         onnxEmbeddingModel = DEFAULT_CONFIG.ONNX_EMBEDDING_MODEL,
-        onnxEmbeddingModelQuantized = DEFAULT_CONFIG.ONNX_EMBEDDING_MODEL_QUANTIZED,
+        dtype = DEFAULT_CONFIG.DTYPE,
+        onnxEmbeddingModelQuantized,
         localModelPath = DEFAULT_CONFIG.LOCAL_MODEL_PATH,
@@ -49,8 +49,12 @@ modelCacheDir = DEFAULT_CONFIG.MODEL_CACHE_DIR,
 
-    // Set env variables if provided
-    if (localModelPath) env.localModelPath = localModelPath;
-    if (modelCacheDir) env.cacheDir = modelCacheDir;
+    // if legacy boolean is used (onnxEmbeddingModelQuantized), set dtype (model precision) to 'q8'
+    if (onnxEmbeddingModelQuantized === true) { dtype = 'q8'; }
 
-    // Initialize embedding utilities
-    const { modelName, isQuantized } = await initializeEmbeddingUtils(onnxEmbeddingModel, onnxEmbeddingModelQuantized);
+    // Initialize embedding utilities and set optional paths
+    const { modelName, dtype: usedDtype } = await initializeEmbeddingUtils(
+        onnxEmbeddingModel, 
+        dtype,
+        localModelPath,
+        modelCacheDir
+    );
 
@@ -102,3 +106,3 @@ // Process each document
                 console.log(`--------------`);
-                console.log(chunk);
+                console.log(chunk.substring(0, 50) + '...');
             });
@@ -119,3 +123,3 @@ }
                     console.log("--------------------");
-                    console.log(chunk);
+                    console.log(chunk.substring(0, 50) + '...');
                 });
@@ -139,3 +143,3 @@ }
                 model_name: modelName,
-                is_model_quantized: isQuantized,
+                dtype: usedDtype,
                 text: prefixedChunk
@@ -186,3 +190,4 @@ };
         onnxEmbeddingModel = DEFAULT_CONFIG.ONNX_EMBEDDING_MODEL,
-        onnxEmbeddingModelQuantized = DEFAULT_CONFIG.ONNX_EMBEDDING_MODEL_QUANTIZED,
+        onnxEmbeddingModelQuantized,
+        dtype = DEFAULT_CONFIG.DTYPE,
         localModelPath = DEFAULT_CONFIG.LOCAL_MODEL_PATH,
@@ -201,8 +206,12 @@ modelCacheDir = DEFAULT_CONFIG.MODEL_CACHE_DIR,
 
-    // Set env variables if provided
-    if (localModelPath) env.localModelPath = localModelPath;
-    if (modelCacheDir) env.cacheDir = modelCacheDir;
+    // if legacy boolean is used (onnxEmbeddingModelQuantized), set dtype (model precision) to 'q8'
+    if (onnxEmbeddingModelQuantized === true) { dtype = 'q8'; }
 
-    // Initialize embedding utilities
-    const { modelName, isQuantized } = await initializeEmbeddingUtils(onnxEmbeddingModel, onnxEmbeddingModelQuantized);
+    // Initialize embedding utilities with paths
+    const { modelName, isQuantized } = await initializeEmbeddingUtils(
+        onnxEmbeddingModel, 
+        onnxEmbeddingModelQuantized,
+        localModelPath,
+        modelCacheDir
+    );
 
@@ -232,3 +241,3 @@ // Process each document
                 console.log(`--------------`);
-                console.log(chunk);
+                console.log(chunk.substring(0, 50) + '...');
             });
@@ -235,0 +244,0 @@ }

config.js

@@ -11,3 +11,3 @@ export const DEFAULT_CONFIG = {
     ONNX_EMBEDDING_MODEL: "Xenova/all-MiniLM-L6-v2",
-    ONNX_EMBEDDING_MODEL_QUANTIZED: true,
+    DTYPE: 'fp32',
     LOCAL_MODEL_PATH: null,
@@ -14,0 +14,0 @@ MODEL_CACHE_DIR: null,

embeddingUtils.js

@@ -1,2 +0,2 @@
-import { env, pipeline, AutoTokenizer } from '@xenova/transformers';
+import { env, pipeline, AutoTokenizer } from '@huggingface/transformers';
 
@@ -10,10 +10,18 @@ let tokenizer;
 // --------------------------------------------
-export async function initializeEmbeddingUtils(onnxEmbeddingModel, onnxEmbeddingModelQuantized) {
+export async function initializeEmbeddingUtils(
+    onnxEmbeddingModel, 
+    dtype = 'fp32',
+    localModelPath = null,
+    modelCacheDir = null
+) {
+    // Configure environment
     env.allowRemoteModels = true;
+    if (localModelPath) env.localModelPath = localModelPath;
+    if (modelCacheDir) env.cacheDir = modelCacheDir;
+
     tokenizer = await AutoTokenizer.from_pretrained(onnxEmbeddingModel);
     generateEmbedding = await pipeline('feature-extraction', onnxEmbeddingModel, {
-        quantized: onnxEmbeddingModelQuantized,
+        dtype: dtype,
     });
 
-    // Clear the embedding cache when initializing with a new model
     embeddingCache.clear();
@@ -23,3 +31,3 @@
         modelName: onnxEmbeddingModel,
-        isQuantized: onnxEmbeddingModelQuantized
+        dtype: dtype
     };
@@ -26,0 +34,0 @@ }

example/example-chunkit.js

@@ -16,3 +16,3 @@ // ------------------------
 let documents = [];
-let textFiles = ['./different.txt', './similar.txt'];
+let textFiles = ['./example.txt', './different.txt', './similar.txt'];
 
@@ -42,3 +42,3 @@ // read each text file and add it to the documents array
         onnxEmbeddingModel: "nomic-ai/nomic-embed-text-v1.5",
-        onnxEmbeddingModelQuantized: true,
+        dtype: "q8",
         localModelPath: "../models",
@@ -60,5 +60,5 @@ modelCacheDir: "../models",
 console.log("\n\n\n");
-console.log("myTestChunks:");
-console.log(myTestChunks);
+// console.log("myTestChunks:");
+// console.log(myTestChunks);
 console.log("length: " + myTestChunks.length);
 console.log("trackedTimeSeconds: " + trackedTimeSeconds);

package.json

 {
   "name": "semantic-chunking",
-  "version": "2.2.4",
+  "version": "2.3.0",
   "description": "Semantically create chunks from large texts. Useful for workflows involving large language models (LLMs).",
@@ -39,3 +39,3 @@ "repository": {
   "dependencies": {
-    "@xenova/transformers": "^2.17.2",
+    "@huggingface/transformers": "^3.0.2",
     "cli-progress": "^3.12.0",
@@ -42,0 +42,0 @@ "fs": "^0.0.1-security",

README.md

@@ -74,3 +74,3 @@ # 🍱 semantic-chunking
   - `onnxEmbeddingModel`: String (optional, default `Xenova/all-MiniLM-L6-v2`) - ONNX model used for creating embeddings.
-  - `onnxEmbeddingModelQuantized`: Boolean (optional, default `true`) - Indicates whether to use a quantized version of the embedding model.
+  - `dtype`: String (optional, default `fp32`) - Precision of the embedding model (options: `fp32`, `fp16`, `q8`, `q4`).
   - `localModelPath`: String (optional, default `null`) - Local path to save and load models (example: `./models`).
@@ -92,3 +92,3 @@ - `modelCacheDir`: String (optional, default `null`) - Directory to cache downloaded models (example: `./models`).
 - `model_name`: String - The name of the embedding model used.
-- `is_model_quantized`: Boolean - Indicates whether the embedding model is quantized.
+- `dtype`: String - The precision of the embedding model used (options: `fp32`, `fp16`, `q8`, `q4`).
 - `text`: String - The chunked text.
@@ -203,3 +203,3 @@ - `embedding`: Array - The embedding vector (if `returnEmbedding` is `true`).
 - **Type**: String
-- **Default**: `Xenova/paraphrase-multilingual-MiniLM-L12-v2`
+- **Default**: `Xenova/all-MiniLM-L6-v2`
 - **Description**: Specifies the model used to generate sentence embeddings. Different models may yield different qualities of embeddings, affecting the chunking quality, especially in multilingual contexts.
@@ -219,14 +219,12 @@ - **Resource Link**: [ONNX Embedding Models](https://huggingface.co/models?pipeline_tag=feature-extraction&library=onnx&sort=trending)
 
-| Model                                        | Quantized | Link                                                                                                                                       | Size    |
-| -------------------------------------------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ------- |
-| nomic-ai/nomic-embed-text-v1.5               | true      | [https://huggingface.co/nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)                             | 138 MB  |
-| nomic-ai/nomic-embed-text-v1.5               | false     | [https://huggingface.co/nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)                             | 548 MB  |
-| Xenova/all-MiniLM-L6-v2                      | true      | [https://huggingface.co/Xenova/all-MiniLM-L6-v2](https://huggingface.co/Xenova/all-MiniLM-L6-v2)                                           | 23 MB   |
-| Xenova/all-MiniLM-L6-v2                      | false     | [https://huggingface.co/Xenova/all-MiniLM-L6-v2](https://huggingface.co/Xenova/all-MiniLM-L6-v2)                                           | 90.4 MB |
-| Xenova/paraphrase-multilingual-MiniLM-L12-v2 | true      | [https://huggingface.co/Xenova/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/Xenova/paraphrase-multilingual-MiniLM-L12-v2) | 118 MB  |
-| thenlper/gte-base                            | false     | [https://huggingface.co/thenlper/gte-base](https://huggingface.co/thenlper/gte-base)                                                       | 436 MB  |
-| Xenova/all-distilroberta-v1                  | true      | [https://huggingface.co/Xenova/all-distilroberta-v1](https://huggingface.co/Xenova/all-distilroberta-v1)                                   | 82.1 MB |
-| Xenova/all-distilroberta-v1                  | false     | [https://huggingface.co/Xenova/all-distilroberta-v1](https://huggingface.co/Xenova/all-distilroberta-v1)                                   | 326 MB  |
-| BAAI/bge-base-en-v1.5                        | false     | [https://huggingface.co/BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                                               | 436 MB  |
-| BAAI/bge-small-en-v1.5                       | false     | [https://huggingface.co/BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5)                                             | 133 MB  |
+| Model                                        | Precision      | Link                                                                                                                                       | Size                   |
+| -------------------------------------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------- |
+| nomic-ai/nomic-embed-text-v1.5               | fp32, q8       | [https://huggingface.co/nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)                             | 548 MB, 138 MB         |
+| thenlper/gte-base                            | fp32           | [https://huggingface.co/thenlper/gte-base](https://huggingface.co/thenlper/gte-base)                                                       | 436 MB                 |
+| Xenova/all-MiniLM-L6-v2                      | fp32, fp16, q8 | [https://huggingface.co/Xenova/all-MiniLM-L6-v2](https://huggingface.co/Xenova/all-MiniLM-L6-v2)                                           | 23 MB, 45 MB, 90 MB    |
+| Xenova/paraphrase-multilingual-MiniLM-L12-v2 | fp32, fp16, q8 | [https://huggingface.co/Xenova/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/Xenova/paraphrase-multilingual-MiniLM-L12-v2) | 470 MB, 235 MB, 118 MB |
+| Xenova/all-distilroberta-v1                  | fp32, fp16, q8 | [https://huggingface.co/Xenova/all-distilroberta-v1](https://huggingface.co/Xenova/all-distilroberta-v1)                                   | 326 MB, 163 MB, 82 MB  |
+| BAAI/bge-base-en-v1.5                        | fp32           | [https://huggingface.co/BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                                               | 436 MB                 |
+| BAAI/bge-small-en-v1.5                       | fp32           | [https://huggingface.co/BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5)                                             | 133 MB                 |
+| yashvardhan7/snowflake-arctic-embed-m-onnx   | fp32           | [https://huggingface.co/yashvardhan7/snowflake-arctic-embed-m-onnx](https://huggingface.co/yashvardhan7/snowflake-arctic-embed-m-onnx)     | 436 MB                 |
 
@@ -337,3 +335,3 @@ Each of these parameters allows you to customize the `chunkit` function to better fit the text size, content complexity, and performance requirements of your application.
 ];
-const myDocumentChunks = await chunkit(documents, { chunkPrefix: "search_document" });
+const myDocumentChunks = await chunkit(documents, { chunkPrefix: "search_document", returnEmbedding: true });
 ```
@@ -346,3 +344,3 @@
 ];
-const mySearchQueryChunk = await chunkit(documents, { chunkPrefix: "search_query" });
+const mySearchQueryChunk = await cramit(documents, { chunkPrefix: "search_query", returnEmbedding: true });
 ```
@@ -349,0 +347,0 @@

similarityUtils.js

@@ -0,0 +0,0 @@ import { createEmbedding } from './embeddingUtils.js';

webui/package-lock.json

 {
   "name": "semantic-chunking-webui",
-  "version": "1.1.4",
+  "version": "1.3.0",
   "lockfileVersion": 3,
@@ -9,8 +9,8 @@ "requires": true,
       "name": "semantic-chunking-webui",
-      "version": "1.1.4",
+      "version": "1.3.0",
       "license": "ISC",
       "dependencies": {
         "cors": "^2.8.5",
-        "express": "^4.18.3",
-        "highlight.js": "^11.10.0"
+        "dotenv": "^16.4.5",
+        "express": "^4.18.3"
       }
@@ -169,2 +169,13 @@ },
     },
+    "node_modules/dotenv": {
+      "version": "16.4.5",
+      "resolved": "https://registry.npmjs.org/dotenv/-/dotenv-16.4.5.tgz",
+      "integrity": "sha512-ZmdL2rui+eB2YwhsWzjInR8LldtZHGDoQ1ugH85ppHKwpUHL7j7rN0Ti9NCnGiQbhaZ11FpR+7ao1dNsmduNUg==",
+      "engines": {
+        "node": ">=12"
+      },
+      "funding": {
+        "url": "https://dotenvx.com"
+      }
+    },
     "node_modules/ee-first": {
@@ -370,10 +381,2 @@ "version": "1.1.1",
     },
-    "node_modules/highlight.js": {
-      "version": "11.10.0",
-      "resolved": "https://registry.npmjs.org/highlight.js/-/highlight.js-11.10.0.tgz",
-      "integrity": "sha512-SYVnVFswQER+zu1laSya563s+F8VDGt7o35d4utbamowvUNLLMovFqwCLSocpZTz3MgaSRA1IbqRWZv97dtErQ==",
-      "engines": {
-        "node": ">=12.0.0"
-      }
-    },
     "node_modules/http-errors": {
@@ -494,5 +497,5 @@ "version": "2.0.0",
     "node_modules/object-inspect": {
-      "version": "1.13.2",
-      "resolved": "https://registry.npmjs.org/object-inspect/-/object-inspect-1.13.2.tgz",
-      "integrity": "sha512-IRZSRuzJiynemAXPYtPe5BoI/RESNYR7TYm50MC5Mqbd3Jmw5y790sErYw3V6SryFJD64b74qQQs9wn5Bg/k3g==",
+      "version": "1.13.3",
+      "resolved": "https://registry.npmjs.org/object-inspect/-/object-inspect-1.13.3.tgz",
+      "integrity": "sha512-kDCGIbxkDSXE3euJZZXzc6to7fCrKHNI/hSRQnRuQ+BWjFNzZwiFF8fj/6o2t2G9/jTj8PSIYTfCLelLZEeRpA==",
       "engines": {
@@ -499,0 +502,0 @@ "node": ">= 0.4"

webui/package.json

 {
   "name": "semantic-chunking-webui",
-  "version": "1.1.4",
+  "version": "1.3.0",
   "type": "module",
@@ -16,5 +16,5 @@ "description": "Web UI for semantic-chunking library",
     "cors": "^2.8.5",
-    "express": "^4.18.3",
-    "highlight.js": "^11.10.0"
+    "dotenv": "^16.4.5",
+    "express": "^4.18.3"
   }
 }

webui/public/main.js

@@ -136,2 +136,12 @@ // Load sample text on page load
 
+// Add this function near the top of the file
+function scrollToResults() {
+    if (window.innerWidth <= 800) {
+        const resultsWrapper = document.querySelector('.results-wrapper');
+        if (resultsWrapper) {
+            resultsWrapper.scrollIntoView({ behavior: 'smooth' });
+        }
+    }
+}
+
 // Process form handler
@@ -151,2 +161,5 @@ form.addEventListener('submit', async (e) => {
         
+        // Scroll to results as soon as we show the spinner
+        scrollToResults();
+
         // Get form data and convert checkbox values to boolean
@@ -260,2 +273,5 @@ const formData = new FormData(form);
         
+        // After results are displayed, scroll to them on mobile
+        scrollToResults();
+        
     } catch (error) {
@@ -266,4 +282,4 @@ console.error('Error:', error);
         if (errorMessage.includes('Could not locate file:')) {
-            errorMessage += '<br><br>Some models may not have both a quantized & non-quantized version,';
-            errorMessage += '<br>please toggle this option and try again, or choose a different model';
+            errorMessage += '<br><br>Not all models have all precision options available.';
+            errorMessage += '<br>Please try a different precision level and/or model and try again.';
         }
@@ -326,3 +342,3 @@
             formData[element.name] = element.checked;
-        } else if (element.name) {  // Only process elements with names
+        } else if (element.name) {
             formData[element.name] = element.value;
@@ -332,7 +348,5 @@ }
     
-    // No need for additional processing in generateCode since we're already
-    // getting the actual boolean values here
     codeExample.textContent = generateCode(formData);
     modal.style.display = "block";
-    // Clear the highlighted state before highlighting again
+    document.body.style.overflow = 'hidden';  // Prevent body scrolling
     delete codeExample.dataset.highlighted;
@@ -344,3 +358,5 @@ hljs.highlightElement(codeExample);
 function generateCode(formData) {
-    // No need to convert checkbox values since they're already booleans
+    const dtypeValues = ['fp32', 'fp16', 'q8', 'q4'];
+    const dtype = dtypeValues[parseInt(formData.dtype)];
+    
     return `// import the semantic-chunking library
@@ -370,3 +386,3 @@ import { chunkit } from 'semantic-chunking';
         onnxEmbeddingModel: "${formData.onnxEmbeddingModel}",
-        onnxEmbeddingModelQuantized: ${formData.onnxEmbeddingModelQuantized},
+        dtype: "${dtype}",
         localModelPath: "./models",
@@ -388,2 +404,3 @@ modelCacheDir: "./models",
     modal.style.display = "none";
+    document.body.style.overflow = '';  // Restore body scrolling
 };
@@ -395,2 +412,3 @@
         modal.style.display = "none";
+        document.body.style.overflow = '';  // Restore body scrolling
     }
@@ -419,2 +437,3 @@ };
     modal.style.display = "none";
+    document.body.style.overflow = '';  // Restore body scrolling
 };
@@ -490,2 +509,30 @@
     resizeToggle.classList.toggle('wrapped');
-});
+});
+
+// Add this to your existing range input handlers
+const dtypeInput = document.getElementById('dtype');
+const dtypeDisplay = dtypeInput.nextElementSibling;
+
+function updateDtypeDisplay(value) {
+    const dtypeValues = {
+        0: { text: 'fp32 - Full Precision', class: 'precision-full' },
+        1: { text: 'fp16 - Half Precision', class: 'precision-half' },
+        2: { text: 'q8 - 8-bit Quantized', class: 'precision-q8' },
+        3: { text: 'q4 - 4-bit Quantized', class: 'precision-q4' }
+    };
+
+    const dtype = dtypeValues[value];
+    const number = dtypeDisplay.querySelector('.number');
+    const description = dtypeDisplay.querySelector('.description');
+    
+    number.className = `number ${dtype.class}`;
+    number.textContent = value;
+    description.className = `description ${dtype.class}`;
+    description.textContent = dtype.text;
+}
+
+// Initial update
+updateDtypeDisplay(dtypeInput.value);
+
+// Update on change
+dtypeInput.addEventListener('input', (e) => updateDtypeDisplay(e.target.value));

webui/public/models.json

@@ -30,4 +30,8 @@ {
       "label": "BAAI/bge-small-en-v1.5"
+    },
+    {
+      "value": "yashvardhan7/snowflake-arctic-embed-m-onnx",
+      "label": "yashvardhan7/snowflake-arctic-embed-m-onnx"
     }
   ]
 }

webui/server.js

@@ -6,3 +6,6 @@ import express from 'express';
 import { chunkit } from '../chunkit.js';
+import dotenv from 'dotenv';
 
+dotenv.config();
+
 const __filename = fileURLToPath(import.meta.url);
@@ -34,12 +37,17 @@ const __dirname = path.dirname(__filename);
     try {
-        const { documentText, documentName, ...options } = req.body;
+        const { documentText, documentName, dtype, onnxEmbeddingModelQuantized, ...options } = req.body;
+        
+        // Convert dtype value to string mapping
+        const dtypeValues = ['fp32', 'fp16', 'q8', 'q4'];
+        const dtypeString = dtypeValues[parseInt(dtype)] || 'fp32';
 
-        // Input validation
-        if (!documentText) {
-            return res.status(400).json({ error: 'Document text is required' });
-        }
+        // Process the text with new dtype option
+        const documents = [{
+            document_name: documentName || 'sample text',
+            document_text: documentText
+        }];
 
-        // Convert string values to appropriate types
         const processedOptions = {
             ...options,
+            dtype: dtypeString,
             maxTokenSize: parseInt(options.maxTokenSize),
@@ -52,3 +60,2 @@ similarityThreshold: parseFloat(options.similarityThreshold),
             combineChunksSimilarityThreshold: parseFloat(options.combineChunksSimilarityThreshold),
-            onnxEmbeddingModelQuantized: options.onnxEmbeddingModelQuantized === true,
             returnEmbedding: options.returnEmbedding === true,
@@ -61,9 +68,3 @@ returnTokenLength: options.returnTokenLength === true,
 
-        // Process the text
-        const documents = [{
-            document_name: documentName || 'sample text',
-            document_text: documentText
-        }];
         const result = await chunkit(documents, processedOptions);
-
         res.json(result);
@@ -70,0 +71,0 @@ } catch (error) {

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Improved metrics

Total package byte prevSize

3506574

increased by5.03%

Number of package files

114

increased by4.59%

Lines of code

3372

increased by3.44%

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Number of lines in readme file

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increased by25%

Dependency changes

• + Added@huggingface/transformers@^3.0.2

• + Added@emnapi/runtime@1.3.1(transitive)

• + Added@huggingface/jinja@0.3.2(transitive)

• + Added@huggingface/transformers@3.2.4(transitive)

• + Added@img/sharp-darwin-arm64@0.33.5(transitive)

• + Added@img/sharp-darwin-x64@0.33.5(transitive)

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