Fixed ci and lint error

Author: xralphack

.github/workflows/ci.yml

@@ -49,16 +49,3 @@ jobs:
 
       - name: Build package
         run: yarn prepare
-
-  build-web:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Setup
-        uses: ./.github/actions/setup
-
-      - name: Build example for Web
-        run: |
-          yarn example expo export --platform web

src/__tests__/text-embedding.pipeline.test.tsx

@@ -11,12 +11,6 @@ jest.mock('../models/text-embedding', () => {
   };
 });
 
-// Create a callable tokenizer mock
-const createCallableTokenizer = () => {
-  const tokenizer = jest.fn().mockResolvedValue({ input_ids: [1n, 2n, 3n] });
-  return tokenizer;
-};
-
 describe('TextEmbedding Pipeline', () => {
   beforeEach(() => {
     jest.clearAllMocks();

src/pipelines/text-embedding.tsx

@@ -1,7 +1,4 @@
-import {
-  env,
-  AutoTokenizer,
-} from '@huggingface/transformers';
+import { env, AutoTokenizer } from '@huggingface/transformers';
 import type { PreTrainedTokenizer } from '@huggingface/transformers';
 import { TextEmbedding as Model } from '../models/text-embedding';
 import type { LoadOptions } from '../models/base';

src/pipelines/text-generation.tsx

@@ -1,7 +1,4 @@
-import {
-  env,
-  AutoTokenizer,
-} from '@huggingface/transformers';
+import { env, AutoTokenizer } from '@huggingface/transformers';
 import type { PreTrainedTokenizer } from '@huggingface/transformers';
 import { TextGeneration as Model } from '../models/text-generation';
 import type { LoadOptions } from '../models/base';

src/types/huggingface-transformers.d.ts

@@ -1,12 +1,18 @@
 declare module '@huggingface/transformers' {
   export interface PreTrainedTokenizer {
-    (text: string, options?: {
-      return_tensor?: boolean;
-      padding?: boolean;
-      truncation?: boolean;
-      max_length?: number;
-    }): Promise<{ input_ids: number[] }>;
-    decode(tokens: number[], options?: { skip_special_tokens?: boolean }): string;
+    (
+      text: string,
+      options?: {
+        return_tensor?: boolean;
+        padding?: boolean;
+        truncation?: boolean;
+        max_length?: number;
+      }
+    ): Promise<{ input_ids: number[] }>;
+    decode(
+      tokens: number[],
+      options?: { skip_special_tokens?: boolean }
+    ): string;
   }
 
   export class AutoTokenizer {