-
Notifications
You must be signed in to change notification settings - Fork 41
/
gptj_arch.txt
455 lines (455 loc) · 21.1 KB
/
gptj_arch.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
GPTJModel(
(wte): Embedding(50400, 4096)
(drop): Dropout(p=0.0, inplace=False)
(h): ModuleList(
(0): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(1): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(2): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(3): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(4): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(5): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(6): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(7): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(8): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(9): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(10): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(11): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(12): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(13): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(14): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(15): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(16): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(17): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(18): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(19): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(20): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(21): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(22): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(23): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(24): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(25): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(26): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(27): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
)
(ln_f): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
)