akhil-vaidya commited on
Commit
e6d784e
1 Parent(s): 6a25d63

updated gitignore

Browse files
Files changed (2) hide show
  1. .gitignore +2 -0
  2. archive/qwen_test.ipynb +0 -324
.gitignore ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ .github/
2
+ .devcontainer/
archive/qwen_test.ipynb DELETED
@@ -1,324 +0,0 @@
1
- {
2
- "cells": [
3
- {
4
- "cell_type": "code",
5
- "execution_count": 1,
6
- "metadata": {},
7
- "outputs": [],
8
- "source": [
9
- "from PIL import Image\n",
10
- "import requests\n",
11
- "import torch\n",
12
- "from torchvision import io\n",
13
- "from typing import Dict\n",
14
- "from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor"
15
- ]
16
- },
17
- {
18
- "cell_type": "code",
19
- "execution_count": 2,
20
- "metadata": {},
21
- "outputs": [
22
- {
23
- "data": {
24
- "application/vnd.jupyter.widget-view+json": {
25
- "model_id": "29ac356cdb05492d8a2da9bceea03b37",
26
- "version_major": 2,
27
- "version_minor": 0
28
- },
29
- "text/plain": [
30
- "config.json: 0%| | 0.00/1.20k [00:00<?, ?B/s]"
31
- ]
32
- },
33
- "metadata": {},
34
- "output_type": "display_data"
35
- },
36
- {
37
- "name": "stderr",
38
- "output_type": "stream",
39
- "text": [
40
- "c:\\Users\\Akhil PC\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\huggingface_hub\\file_download.py:157: UserWarning: `huggingface_hub` cache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them in C:\\Users\\Akhil PC\\.cache\\huggingface\\hub\\models--Qwen--Qwen2-VL-2B-Instruct. Caching files will still work but in a degraded version that might require more space on your disk. This warning can be disabled by setting the `HF_HUB_DISABLE_SYMLINKS_WARNING` environment variable. For more details, see https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations.\n",
41
- "To support symlinks on Windows, you either need to activate Developer Mode or to run Python as an administrator. In order to see activate developer mode, see this article: https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development\n",
42
- " warnings.warn(message)\n",
43
- "Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}\n"
44
- ]
45
- },
46
- {
47
- "data": {
48
- "application/vnd.jupyter.widget-view+json": {
49
- "model_id": "3ca08388cd3a4bc58b5b3c84b57fcd7f",
50
- "version_major": 2,
51
- "version_minor": 0
52
- },
53
- "text/plain": [
54
- "model.safetensors.index.json: 0%| | 0.00/56.4k [00:00<?, ?B/s]"
55
- ]
56
- },
57
- "metadata": {},
58
- "output_type": "display_data"
59
- },
60
- {
61
- "data": {
62
- "application/vnd.jupyter.widget-view+json": {
63
- "model_id": "7f667bff4c014fce85cb222f40508c78",
64
- "version_major": 2,
65
- "version_minor": 0
66
- },
67
- "text/plain": [
68
- "Downloading shards: 0%| | 0/2 [00:00<?, ?it/s]"
69
- ]
70
- },
71
- "metadata": {},
72
- "output_type": "display_data"
73
- },
74
- {
75
- "data": {
76
- "application/vnd.jupyter.widget-view+json": {
77
- "model_id": "c4289d2bd8f0466586d20564fb8fef84",
78
- "version_major": 2,
79
- "version_minor": 0
80
- },
81
- "text/plain": [
82
- "model-00001-of-00002.safetensors: 0%| | 0.00/3.99G [00:00<?, ?B/s]"
83
- ]
84
- },
85
- "metadata": {},
86
- "output_type": "display_data"
87
- },
88
- {
89
- "data": {
90
- "application/vnd.jupyter.widget-view+json": {
91
- "model_id": "47d67996509f431abb0f99bab97a03d6",
92
- "version_major": 2,
93
- "version_minor": 0
94
- },
95
- "text/plain": [
96
- "model-00002-of-00002.safetensors: 0%| | 0.00/429M [00:00<?, ?B/s]"
97
- ]
98
- },
99
- "metadata": {},
100
- "output_type": "display_data"
101
- },
102
- {
103
- "name": "stderr",
104
- "output_type": "stream",
105
- "text": [
106
- "`Qwen2VLRotaryEmbedding` can now be fully parameterized by passing the model config through the `config` argument. All other arguments will be removed in v4.46\n"
107
- ]
108
- },
109
- {
110
- "data": {
111
- "application/vnd.jupyter.widget-view+json": {
112
- "model_id": "d3e49e52f64147e2b5043c76d9a507e6",
113
- "version_major": 2,
114
- "version_minor": 0
115
- },
116
- "text/plain": [
117
- "Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]"
118
- ]
119
- },
120
- "metadata": {},
121
- "output_type": "display_data"
122
- },
123
- {
124
- "data": {
125
- "application/vnd.jupyter.widget-view+json": {
126
- "model_id": "5060e7d44d5b40fd8ca2d7e90542be21",
127
- "version_major": 2,
128
- "version_minor": 0
129
- },
130
- "text/plain": [
131
- "generation_config.json: 0%| | 0.00/272 [00:00<?, ?B/s]"
132
- ]
133
- },
134
- "metadata": {},
135
- "output_type": "display_data"
136
- },
137
- {
138
- "data": {
139
- "application/vnd.jupyter.widget-view+json": {
140
- "model_id": "ac0500d6289442d88db22065e94c6df2",
141
- "version_major": 2,
142
- "version_minor": 0
143
- },
144
- "text/plain": [
145
- "preprocessor_config.json: 0%| | 0.00/347 [00:00<?, ?B/s]"
146
- ]
147
- },
148
- "metadata": {},
149
- "output_type": "display_data"
150
- },
151
- {
152
- "data": {
153
- "application/vnd.jupyter.widget-view+json": {
154
- "model_id": "99ff45911ba848f2bd3ccd3f57029641",
155
- "version_major": 2,
156
- "version_minor": 0
157
- },
158
- "text/plain": [
159
- "tokenizer_config.json: 0%| | 0.00/4.19k [00:00<?, ?B/s]"
160
- ]
161
- },
162
- "metadata": {},
163
- "output_type": "display_data"
164
- },
165
- {
166
- "data": {
167
- "application/vnd.jupyter.widget-view+json": {
168
- "model_id": "9d484f67779348d7b242a12de0505324",
169
- "version_major": 2,
170
- "version_minor": 0
171
- },
172
- "text/plain": [
173
- "vocab.json: 0%| | 0.00/2.78M [00:00<?, ?B/s]"
174
- ]
175
- },
176
- "metadata": {},
177
- "output_type": "display_data"
178
- },
179
- {
180
- "data": {
181
- "application/vnd.jupyter.widget-view+json": {
182
- "model_id": "b0e6345cf4cd4b61b7d6b10ab7ae6f23",
183
- "version_major": 2,
184
- "version_minor": 0
185
- },
186
- "text/plain": [
187
- "merges.txt: 0%| | 0.00/1.67M [00:00<?, ?B/s]"
188
- ]
189
- },
190
- "metadata": {},
191
- "output_type": "display_data"
192
- },
193
- {
194
- "data": {
195
- "application/vnd.jupyter.widget-view+json": {
196
- "model_id": "c108ffe24eab4d82a8aa8d5bda088bf7",
197
- "version_major": 2,
198
- "version_minor": 0
199
- },
200
- "text/plain": [
201
- "tokenizer.json: 0%| | 0.00/7.03M [00:00<?, ?B/s]"
202
- ]
203
- },
204
- "metadata": {},
205
- "output_type": "display_data"
206
- },
207
- {
208
- "data": {
209
- "application/vnd.jupyter.widget-view+json": {
210
- "model_id": "c9385ab1782f49fcb59fbe2aa73a81c5",
211
- "version_major": 2,
212
- "version_minor": 0
213
- },
214
- "text/plain": [
215
- "chat_template.json: 0%| | 0.00/1.05k [00:00<?, ?B/s]"
216
- ]
217
- },
218
- "metadata": {},
219
- "output_type": "display_data"
220
- }
221
- ],
222
- "source": [
223
- "# Load the model in half-precision on the available device(s)\n",
224
- "model = Qwen2VLForConditionalGeneration.from_pretrained(\"Qwen/Qwen2-VL-2B-Instruct\", device_map=\"cpu\", torch_dtype=torch.float16)\n",
225
- "processor = AutoProcessor.from_pretrained(\"Qwen/Qwen2-VL-2B-Instruct\")"
226
- ]
227
- },
228
- {
229
- "cell_type": "code",
230
- "execution_count": 3,
231
- "metadata": {},
232
- "outputs": [],
233
- "source": [
234
- "# Image\n",
235
- "url = \"https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg\"\n",
236
- "image = Image.open(requests.get(url, stream=True).raw)\n",
237
- "\n",
238
- "conversation = [\n",
239
- " {\n",
240
- " \"role\":\"user\",\n",
241
- " \"content\":[\n",
242
- " {\n",
243
- " \"type\":\"image\",\n",
244
- " },\n",
245
- " {\n",
246
- " \"type\":\"text\",\n",
247
- " \"text\":\"Describe this image.\"\n",
248
- " }\n",
249
- " ]\n",
250
- " }\n",
251
- "]"
252
- ]
253
- },
254
- {
255
- "cell_type": "code",
256
- "execution_count": 4,
257
- "metadata": {},
258
- "outputs": [],
259
- "source": [
260
- "# Preprocess the inputs\n",
261
- "text_prompt = processor.apply_chat_template(conversation, add_generation_prompt=True)"
262
- ]
263
- },
264
- {
265
- "cell_type": "code",
266
- "execution_count": 5,
267
- "metadata": {},
268
- "outputs": [],
269
- "source": [
270
- "inputs = processor(text=[text_prompt], images=[image], padding=True, return_tensors=\"pt\")\n",
271
- "# inputs = inputs.to('cuda')"
272
- ]
273
- },
274
- {
275
- "cell_type": "code",
276
- "execution_count": null,
277
- "metadata": {},
278
- "outputs": [],
279
- "source": [
280
- "# Inference: Generation of the output\n",
281
- "output_ids = model.generate(**inputs, max_new_tokens=128)\n",
282
- "generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(inputs.input_ids, output_ids)]"
283
- ]
284
- },
285
- {
286
- "cell_type": "code",
287
- "execution_count": null,
288
- "metadata": {},
289
- "outputs": [],
290
- "source": [
291
- "output_text = processor.batch_decode(generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True)\n",
292
- "print(output_text)"
293
- ]
294
- },
295
- {
296
- "cell_type": "code",
297
- "execution_count": null,
298
- "metadata": {},
299
- "outputs": [],
300
- "source": []
301
- }
302
- ],
303
- "metadata": {
304
- "kernelspec": {
305
- "display_name": "Python 3",
306
- "language": "python",
307
- "name": "python3"
308
- },
309
- "language_info": {
310
- "codemirror_mode": {
311
- "name": "ipython",
312
- "version": 3
313
- },
314
- "file_extension": ".py",
315
- "mimetype": "text/x-python",
316
- "name": "python",
317
- "nbconvert_exporter": "python",
318
- "pygments_lexer": "ipython3",
319
- "version": "3.12.0"
320
- }
321
- },
322
- "nbformat": 4,
323
- "nbformat_minor": 2
324
- }