Feat: Add voxtral, magistral small 1.1, and misc gemma3n fixes (#2979)

* fix: lock version in gemma3n docs

* feat: add sample configs and docs

* chore: move mistraltokenizer into mistral folder

* feat: update instructions

* feat: add dynamic load voxtral

* fix: remove incorrect vision config, add audio

* fix: support voxtral processing strategy and address none in data

* feat: patch mistraltokenizer subclass upstream and add missing

* feat: update cce commit to include voxtral

* fix: remove old comment

* fix: gemma3 patch not needed anymore

* fix: voxtral modeling code

* fix: remove incorrect ds path

* fix: adjust apply chat template parsing

* feat: enable voxtral patch

* fix: patch

* feat: update example datasets

* fix: target layer

* feat: update gemma3n docs

* feat: update voxtral docs

* feat: revert assistant parsing to rely on new upstream changes

* chore: skip test till next PR fix

* fix: override upstream decode due to missing handling

* feat: update readme

* fix: update

* feat: add magistral small think support

* feat: update mistral-common dep

* fix: lint

* fix: remove optional dep

* chore: typing

* chore: simply import

* feat(doc): update differences for 2507

* fix: coderrabbit comments

* feat: update clarify docs on new transformers

examples/voxtral/voxtral-mini-qlora.yml

@@ -0,0 +1,73 @@
+base_model: mistralai/Voxtral-Mini-3B-2507
+
+# Automatically upload checkpoint and final model to HF
+# hub_model_id: username/custom_model_name
+
+# Enable to use mistral-common tokenizer
+tokenizer_use_mistral_common: true
+
+plugins:
+  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+
+load_in_8bit: false
+load_in_4bit: true
+
+# for use with fft to only train on language model layers
+# unfrozen_parameters:
+  # - language_model.model.*
+  # - lm_head
+  # - embed_tokens
+
+eot_tokens:
+  - <end_of_turn>
+datasets:
+  - path: cgato/SlimOrcaDedupCleaned
+    type: chat_template
+    split: train[:1%]
+    field_messages: conversations
+    message_property_mappings:
+      role: from
+      content: value
+
+val_set_size: 0.0
+output_dir: ./outputs/out
+
+adapter: qlora
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules: 'language_model.model.layers.[\d]+.(mlp|self_attn).(up|down|gate|q|k|v|o)_proj'
+
+sequence_len: 2048
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+micro_batch_size: 1
+num_epochs: 4
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+bf16: auto
+tf32: true
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+resume_from_checkpoint:
+logging_steps: 1
+flash_attention: true
+
+warmup_ratio: 0.1
+evals_per_epoch:
+saves_per_epoch: 1
+weight_decay: 0.0
+special_tokens: