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dolphin-2.9-mixtral-8x22b

Text Generation
Transformers
Safetensors
10 datasets
English
mixtral
Generated from Trainer
axolotl
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
2
Crystalcareai commited on
Commit
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  1. README.md +604 -0
  2. added_tokens.json +4 -0
  3. config.json +31 -0
  4. generation_config.json +7 -0
  5. model-00001-of-00059.safetensors +3 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: mistral-community/Mixtral-8x22B-v0.1
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: out
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: mistral-community/Mixtral-8x22B-v0.1
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ trust_remote_code: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ unfrozen_parameters:
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+ - ^lm_head.weight$
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+ - ^model.embed_tokens.weight$
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+ - model.layers.0.self_attn.q_proj
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+ - model.layers.11.block_sparse_moe.experts.3.w3
253
+ - model.layers.12.block_sparse_moe.experts.3.w3
254
+ - model.layers.13.block_sparse_moe.experts.3.w3
255
+ - model.layers.3.block_sparse_moe.experts.4.w1
256
+ - model.layers.2.block_sparse_moe.experts.4.w1
257
+ - model.layers.1.block_sparse_moe.experts.4.w1
258
+ - model.layers.0.block_sparse_moe.experts.4.w1
259
+ - model.layers.4.block_sparse_moe.experts.4.w1
260
+ - model.layers.5.block_sparse_moe.experts.4.w1
261
+ - model.layers.6.block_sparse_moe.experts.4.w1
262
+ - model.layers.7.block_sparse_moe.experts.4.w1
263
+ - model.layers.8.block_sparse_moe.experts.4.w1
264
+ - model.layers.9.block_sparse_moe.experts.4.w1
265
+ - model.layers.10.block_sparse_moe.experts.4.w1
266
+ - model.layers.11.block_sparse_moe.experts.4.w1
267
+ - model.layers.12.block_sparse_moe.experts.4.w1
268
+ - model.layers.13.block_sparse_moe.experts.4.w1
269
+ - model.layers.2.block_sparse_moe.experts.4.w2
270
+ - model.layers.3.block_sparse_moe.experts.4.w2
271
+ - model.layers.1.block_sparse_moe.experts.4.w2
272
+ - model.layers.20.block_sparse_moe.experts.4.w2
273
+ - model.layers.0.block_sparse_moe.experts.4.w2
274
+ - model.layers.4.block_sparse_moe.experts.4.w2
275
+ - model.layers.5.block_sparse_moe.experts.4.w2
276
+ - model.layers.6.block_sparse_moe.experts.4.w2
277
+ - model.layers.7.block_sparse_moe.experts.4.w2
278
+ - model.layers.8.block_sparse_moe.experts.4.w2
279
+ - model.layers.9.block_sparse_moe.experts.4.w2
280
+ - model.layers.10.block_sparse_moe.experts.4.w2
281
+ - model.layers.11.block_sparse_moe.experts.4.w2
282
+ - model.layers.12.block_sparse_moe.experts.4.w2
283
+ - model.layers.3.block_sparse_moe.experts.4.w3
284
+ - model.layers.2.block_sparse_moe.experts.4.w3
285
+ - model.layers.1.block_sparse_moe.experts.4.w3
286
+ - model.layers.0.block_sparse_moe.experts.4.w3
287
+ - model.layers.4.block_sparse_moe.experts.4.w3
288
+ - model.layers.5.block_sparse_moe.experts.4.w3
289
+ - model.layers.6.block_sparse_moe.experts.4.w3
290
+ - model.layers.7.block_sparse_moe.experts.4.w3
291
+ - model.layers.8.block_sparse_moe.experts.4.w3
292
+ - model.layers.9.block_sparse_moe.experts.4.w3
293
+ - model.layers.10.block_sparse_moe.experts.4.w3
294
+ - model.layers.11.block_sparse_moe.experts.4.w3
295
+ - model.layers.12.block_sparse_moe.experts.4.w3
296
+ - model.layers.13.block_sparse_moe.experts.4.w3
297
+ - model.layers.4.block_sparse_moe.experts.5.w1
298
+ - model.layers.3.block_sparse_moe.experts.5.w1
299
+ - model.layers.2.block_sparse_moe.experts.5.w1
300
+ - model.layers.1.block_sparse_moe.experts.5.w1
301
+ - model.layers.0.block_sparse_moe.experts.5.w1
302
+ - model.layers.5.block_sparse_moe.experts.5.w1
303
+ - model.layers.6.block_sparse_moe.experts.5.w1
304
+ - model.layers.7.block_sparse_moe.experts.5.w1
305
+ - model.layers.8.block_sparse_moe.experts.5.w1
306
+ - model.layers.9.block_sparse_moe.experts.5.w1
307
+ - model.layers.10.block_sparse_moe.experts.5.w1
308
+ - model.layers.11.block_sparse_moe.experts.5.w1
309
+ - model.layers.12.block_sparse_moe.experts.5.w1
310
+ - model.layers.13.block_sparse_moe.experts.5.w1
311
+ - model.layers.4.block_sparse_moe.experts.5.w2
312
+ - model.layers.2.block_sparse_moe.experts.5.w2
313
+ - model.layers.3.block_sparse_moe.experts.5.w2
314
+ - model.layers.1.block_sparse_moe.experts.5.w2
315
+ - model.layers.0.block_sparse_moe.experts.5.w2
316
+ - model.layers.5.block_sparse_moe.experts.5.w2
317
+ - model.layers.6.block_sparse_moe.experts.5.w2
318
+ - model.layers.7.block_sparse_moe.experts.5.w2
319
+ - model.layers.8.block_sparse_moe.experts.5.w2
320
+ - model.layers.9.block_sparse_moe.experts.5.w2
321
+ - model.layers.10.block_sparse_moe.experts.5.w2
322
+ - model.layers.11.block_sparse_moe.experts.5.w2
323
+ - model.layers.12.block_sparse_moe.experts.5.w2
324
+ - model.layers.13.block_sparse_moe.experts.5.w2
325
+ - model.layers.4.block_sparse_moe.experts.5.w3
326
+ - model.layers.3.block_sparse_moe.experts.5.w3
327
+ - model.layers.2.block_sparse_moe.experts.5.w3
328
+ - model.layers.1.block_sparse_moe.experts.5.w3
329
+ - model.layers.0.block_sparse_moe.experts.5.w3
330
+ - model.layers.5.block_sparse_moe.experts.5.w3
331
+ - model.layers.6.block_sparse_moe.experts.5.w3
332
+ - model.layers.7.block_sparse_moe.experts.5.w3
333
+ - model.layers.8.block_sparse_moe.experts.5.w3
334
+ - model.layers.9.block_sparse_moe.experts.5.w3
335
+ - model.layers.10.block_sparse_moe.experts.5.w3
336
+ - model.layers.11.block_sparse_moe.experts.5.w3
337
+ - model.layers.12.block_sparse_moe.experts.5.w3
338
+ - model.layers.13.block_sparse_moe.experts.5.w3
339
+ - model.layers.5.block_sparse_moe.experts.6.w1
340
+ - model.layers.4.block_sparse_moe.experts.6.w1
341
+ - model.layers.3.block_sparse_moe.experts.6.w1
342
+ - model.layers.2.block_sparse_moe.experts.6.w1
343
+ - model.layers.1.block_sparse_moe.experts.6.w1
344
+ - model.layers.0.block_sparse_moe.experts.6.w1
345
+ - model.layers.6.block_sparse_moe.experts.6.w1
346
+ - model.layers.7.block_sparse_moe.experts.6.w1
347
+ - model.layers.8.block_sparse_moe.experts.6.w1
348
+ - model.layers.9.block_sparse_moe.experts.6.w1
349
+ - model.layers.10.block_sparse_moe.experts.6.w1
350
+ - model.layers.11.block_sparse_moe.experts.6.w1
351
+ - model.layers.12.block_sparse_moe.experts.6.w1
352
+ - model.layers.13.block_sparse_moe.experts.6.w1
353
+ - model.layers.5.block_sparse_moe.experts.6.w2
354
+ - model.layers.4.block_sparse_moe.experts.6.w2
355
+ - model.layers.2.block_sparse_moe.experts.6.w2
356
+ - model.layers.3.block_sparse_moe.experts.6.w2
357
+ - model.layers.1.block_sparse_moe.experts.6.w2
358
+ - model.layers.0.block_sparse_moe.experts.6.w2
359
+ - model.layers.6.block_sparse_moe.experts.6.w2
360
+ - model.layers.7.block_sparse_moe.experts.6.w2
361
+ - model.layers.8.block_sparse_moe.experts.6.w2
362
+ - model.layers.9.block_sparse_moe.experts.6.w2
363
+ - model.layers.10.block_sparse_moe.experts.6.w2
364
+ - model.layers.11.block_sparse_moe.experts.6.w2
365
+ - model.layers.12.block_sparse_moe.experts.6.w2
366
+ - model.layers.13.block_sparse_moe.experts.6.w2
367
+ - model.layers.5.block_sparse_moe.experts.6.w3
368
+ - model.layers.4.block_sparse_moe.experts.6.w3
369
+ - model.layers.3.block_sparse_moe.experts.6.w3
370
+ - model.layers.2.block_sparse_moe.experts.6.w3
371
+ - model.layers.1.block_sparse_moe.experts.6.w3
372
+ - model.layers.0.block_sparse_moe.experts.6.w3
373
+ - model.layers.6.block_sparse_moe.experts.6.w3
374
+ - model.layers.7.block_sparse_moe.experts.6.w3
375
+ - model.layers.8.block_sparse_moe.experts.6.w3
376
+ - model.layers.9.block_sparse_moe.experts.6.w3
377
+ - model.layers.10.block_sparse_moe.experts.6.w3
378
+ - model.layers.11.block_sparse_moe.experts.6.w3
379
+ - model.layers.12.block_sparse_moe.experts.6.w3
380
+ - model.layers.13.block_sparse_moe.experts.6.w3
381
+ - model.layers.5.block_sparse_moe.experts.7.w1
382
+ - model.layers.6.block_sparse_moe.experts.7.w1
383
+ - model.layers.3.block_sparse_moe.experts.7.w1
384
+ - model.layers.4.block_sparse_moe.experts.7.w1
385
+ - model.layers.2.block_sparse_moe.experts.7.w1
386
+ - model.layers.0.block_sparse_moe.experts.7.w1
387
+ - model.layers.7.block_sparse_moe.experts.7.w1
388
+ - model.layers.8.block_sparse_moe.experts.7.w1
389
+ - model.layers.9.block_sparse_moe.experts.7.w1
390
+ - model.layers.10.block_sparse_moe.experts.7.w1
391
+ - model.layers.11.block_sparse_moe.experts.7.w1
392
+ - model.layers.12.block_sparse_moe.experts.7.w1
393
+ - model.layers.13.block_sparse_moe.experts.7.w1
394
+ - model.layers.14.block_sparse_moe.experts.7.w1
395
+ - model.layers.6.block_sparse_moe.experts.7.w2
396
+ - model.layers.5.block_sparse_moe.experts.7.w2
397
+ - model.layers.4.block_sparse_moe.experts.7.w2
398
+ - model.layers.2.block_sparse_moe.experts.7.w2
399
+ - model.layers.3.block_sparse_moe.experts.7.w2
400
+ - model.layers.1.block_sparse_moe.experts.7.w2
401
+ - model.layers.0.block_sparse_moe.experts.7.w2
402
+ - model.layers.7.block_sparse_moe.experts.7.w2
403
+ - model.layers.8.block_sparse_moe.experts.7.w2
404
+ - model.layers.9.block_sparse_moe.experts.7.w2
405
+ - model.layers.10.block_sparse_moe.experts.7.w2
406
+ - model.layers.11.block_sparse_moe.experts.7.w2
407
+ - model.layers.12.block_sparse_moe.experts.7.w2
408
+ - model.layers.13.block_sparse_moe.experts.7.w2
409
+ - model.layers.6.block_sparse_moe.experts.7.w3
410
+ - model.layers.5.block_sparse_moe.experts.7.w3
411
+ - model.layers.4.block_sparse_moe.experts.7.w3
412
+ - model.layers.3.block_sparse_moe.experts.7.w3
413
+ - model.layers.2.block_sparse_moe.experts.7.w3
414
+ - model.layers.0.block_sparse_moe.experts.7.w3
415
+ - model.layers.7.block_sparse_moe.experts.7.w3
416
+ - model.layers.8.block_sparse_moe.experts.7.w3
417
+ - model.layers.9.block_sparse_moe.experts.7.w3
418
+ - model.layers.10.block_sparse_moe.experts.7.w3
419
+ - model.layers.11.block_sparse_moe.experts.7.w3
420
+ - model.layers.12.block_sparse_moe.experts.7.w3
421
+ - model.layers.13.block_sparse_moe.experts.7.w3
422
+ - model.layers.14.block_sparse_moe.experts.7.w3
423
+ # - model.layers.0.block_sparse_moe.gate
424
+ # - model.layers.1.block_sparse_moe.gate
425
+ # - model.layers.2.block_sparse_moe.gate
426
+ # - model.layers.3.block_sparse_moe.gate
427
+ # - model.layers.4.block_sparse_moe.gate
428
+ # - model.layers.5.block_sparse_moe.gate
429
+ # - model.layers.6.block_sparse_moe.gate
430
+ # - model.layers.7.block_sparse_moe.gate
431
+ # - model.layers.8.block_sparse_moe.gate
432
+ # - model.layers.9.block_sparse_moe.gate
433
+ # - model.layers.10.block_sparse_moe.gate
434
+ # - model.layers.11.block_sparse_moe.gate
435
+ # - model.layers.12.block_sparse_moe.gate
436
+ # - model.layers.13.block_sparse_moe.gate
437
+
438
+ model_config:
439
+ output_router_logits: true
440
+
441
+ datasets:
442
+ - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
443
+ type: sharegpt
444
+ conversation: chatml
445
+ - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
446
+ type: sharegpt
447
+ conversation: chatml
448
+ - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
449
+ type: sharegpt
450
+ conversation: chatml
451
+ - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
452
+ type: sharegpt
453
+ conversation: chatml
454
+ - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
455
+ type: sharegpt
456
+ conversation: chatml
457
+ - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
458
+ type: sharegpt
459
+ conversation: chatml
460
+ - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
461
+ type: sharegpt
462
+ conversation: chatml
463
+ - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
464
+ type: sharegpt
465
+ conversation: chatml
466
+ - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
467
+ type: sharegpt
468
+ conversation: chatml
469
+ - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
470
+ type: sharegpt
471
+ conversation: chatml
472
+ - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
473
+ type: sharegpt
474
+ conversation: chatml
475
+ - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
476
+ type: sharegpt
477
+ conversation: chatml
478
+ - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
479
+ type: sharegpt
480
+ conversation: chatml
481
+ - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
482
+ type: sharegpt
483
+ conversation: chatml
484
+ - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
485
+ type: sharegpt
486
+ conversation: chatml
487
+
488
+ chat_template: chatml
489
+
490
+ dataset_prepared_path: thingy
491
+ val_set_size: 0.0002
492
+ output_dir: ./out
493
+
494
+ sequence_len: 4096
495
+ sample_packing: true
496
+ pad_to_sequence_len: true
497
+
498
+ gradient_accumulation_steps: 8
499
+ micro_batch_size: 4
500
+ num_epochs: 3
501
+ logging_steps: 1
502
+ optimizer: paged_adamw_8bit
503
+ lr_scheduler: cosine
504
+ learning_rate: 2.7e-5
505
+
506
+ wandb_project: dolphin-2.9-mixtral-8x22b
507
+ wandb_watch:
508
+ wandb_run_id:
509
+ wandb_log_model:
510
+
511
+ train_on_inputs: false
512
+ group_by_length: false
513
+ bf16: auto
514
+ fp16:
515
+ tf32: true
516
+
517
+ gradient_checkpointing: true
518
+ gradient_checkpointing_kwargs:
519
+ use_reentrant: false
520
+ early_stopping_patience:
521
+ # resume_from_checkpoint: /home/ehartford/axolotl/out/checkpoint-316
522
+ local_rank:
523
+ logging_steps: 1
524
+ xformers_attention:
525
+ flash_attention: true
526
+ saves_per_epoch: 8
527
+ save_total_limit: 2
528
+ save_steps:
529
+ evals_per_epoch: 4
530
+ eval_sample_packing: false
531
+ debug:
532
+ deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
533
+ weight_decay: 0.05
534
+ fsdp:
535
+ fsdp_config:
536
+ special_tokens:
537
+ eos_token: "<|im_end|>"
538
+ tokens:
539
+ - "<|im_start|>"
540
+ ```
541
+
542
+ </details><br>
543
+
544
+ # out
545
+
546
+ This model is a fine-tuned version of [mistral-community/Mixtral-8x22B-v0.1](https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1) on the None dataset.
547
+ It achieves the following results on the evaluation set:
548
+ - Loss: 0.5217
549
+
550
+ ## Model description
551
+
552
+ More information needed
553
+
554
+ ## Intended uses & limitations
555
+
556
+ More information needed
557
+
558
+ ## Training and evaluation data
559
+
560
+ More information needed
561
+
562
+ ## Training procedure
563
+
564
+ ### Training hyperparameters
565
+
566
+ The following hyperparameters were used during training:
567
+ - learning_rate: 2.7e-05
568
+ - train_batch_size: 4
569
+ - eval_batch_size: 4
570
+ - seed: 42
571
+ - distributed_type: multi-GPU
572
+ - num_devices: 8
573
+ - gradient_accumulation_steps: 8
574
+ - total_train_batch_size: 256
575
+ - total_eval_batch_size: 32
576
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
577
+ - lr_scheduler_type: cosine
578
+ - lr_scheduler_warmup_steps: 2
579
+ - num_epochs: 3
580
+
581
+ ### Training results
582
+
583
+ | Training Loss | Epoch | Step | Validation Loss |
584
+ |:-------------:|:-----:|:----:|:---------------:|
585
+ | 0.7022 | 0.0 | 1 | 0.6989 |
586
+ | 0.5344 | 0.25 | 238 | 0.5138 |
587
+ | 0.5204 | 0.5 | 476 | 0.5018 |
588
+ | 0.5059 | 0.75 | 714 | 0.4951 |
589
+ | 0.5112 | 1.0 | 952 | 0.4911 |
590
+ | 0.4561 | 1.24 | 1190 | 0.4978 |
591
+ | 0.478 | 1.49 | 1428 | 0.4935 |
592
+ | 0.4714 | 1.74 | 1666 | 0.4899 |
593
+ | 0.4626 | 1.99 | 1904 | 0.4861 |
594
+ | 0.3675 | 2.22 | 2142 | 0.5240 |
595
+ | 0.3595 | 2.47 | 2380 | 0.5229 |
596
+ | 0.3438 | 2.72 | 2618 | 0.5217 |
597
+
598
+
599
+ ### Framework versions
600
+
601
+ - Transformers 4.40.0.dev0
602
+ - Pytorch 2.2.2+cu121
603
+ - Datasets 2.15.0
604
+ - Tokenizers 0.15.0
added_tokens.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "<|im_end|>": 32000,
3
+ "<|im_start|>": 32001
4
+ }
config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "mistral-community/Mixtral-8x22B-v0.1",
3
+ "architectures": [
4
+ "MixtralForCausalLM"
5
+ ],
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 32000,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 6144,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 16384,
13
+ "max_position_embeddings": 65536,
14
+ "model_type": "mixtral",
15
+ "num_attention_heads": 48,
16
+ "num_experts_per_tok": 2,
17
+ "num_hidden_layers": 56,
18
+ "num_key_value_heads": 8,
19
+ "num_local_experts": 8,
20
+ "output_router_logits": true,
21
+ "rms_norm_eps": 1e-05,
22
+ "rope_theta": 1000000,
23
+ "router_aux_loss_coef": 0.001,
24
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