Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- README.md +100 -0
- adapter_config.json +42 -0
- added_tokens.json +3 -0
- chat_template.jinja +47 -0
- checkpoint-4528/added_tokens.json +3 -0
- checkpoint-4528/chat_template.jinja +47 -0
- checkpoint-4528/config.json +54 -0
- checkpoint-4528/generation_config.json +11 -0
- checkpoint-4528/model.safetensors +3 -0
- checkpoint-4528/optimizer.pt +3 -0
- checkpoint-4528/rng_state.pth +3 -0
- checkpoint-4528/scheduler.pt +3 -0
- checkpoint-4528/special_tokens_map.json +33 -0
- checkpoint-4528/tokenizer.json +3 -0
- checkpoint-4528/tokenizer.model +3 -0
- checkpoint-4528/tokenizer_config.json +0 -0
- checkpoint-4528/trainer_state.json +0 -0
- checkpoint-4528/training_args.bin +3 -0
- config.json +54 -0
- generation_config.json +11 -0
- model.safetensors +3 -0
- special_tokens_map.json +33 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
.gitattributes
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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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checkpoint-4528/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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+
library_name: transformers
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license: gemma
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base_model: google/gemma-3-270m-it
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tags:
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- generated_from_trainer
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+
datasets:
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- Humenuik/train.jsonl
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model-index:
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- name: workspace/output/finetune-gemma3-270m-it
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results: []
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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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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.13.0.dev0`
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```yaml
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base_model: google/gemma-3-270m-it
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model_type: GemmaForCausalLM
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tokenizer_type: AutoTokenizer
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+
trust_remote_code: true
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+
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datasets:
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- path: Humenuik/train.jsonl
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type: alpaca
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conversation: "alpaca"
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+
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+
dataset_prepared_path:
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/workspace/output/prepared
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+
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output_dir: /workspace/output/finetune-gemma3-270m-it
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+
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+
lora_r: 32 # Set the LoRA rank, influencing the capacity of the adapter layers.
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+
lora_alpha: 16 # Adjust the LoRA alpha, a scaling factor for LoRA updates.
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+
lora_dropout: 0.05 # Apply a dropout rate to LoRA layers for regularization.
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+
lora_target_modules:
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- q_proj
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+
- v_proj
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- k_proj
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+
- o_proj
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+
- gate_proj
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+
- up_proj
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+
- down_proj # Specify the modules within the model where LoRA adapters will be applied (e.g., attention projections, MLP layers).
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+
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+
gradient_checkpointing: false
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micro_batch_size: 8 # Define the size of each micro-batch processed by the GPU.
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num_epochs: 2 # Set the number of training epochs.
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+
learning_rate: 0.0002 # Specify the learning rate for the optimizer.
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+
lr_scheduler: cosine # Choose a learning rate scheduler (e.g., cosine).
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+
warmup_steps: 10 # Configure warmup steps for the learning rate scheduler.
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batch_size: 24
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gradient_checkpointing: true # Enable gradient checkpointing to reduce memory consumption during training.
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```
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</details><br>
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# workspace/output/finetune-gemma3-270m-it
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This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it) on the Humenuik/train.jsonl dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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+
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- training_steps: 4528
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### Training results
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+
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|
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|
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### Framework versions
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- Transformers 4.55.2
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- Pytorch 2.7.1+cu126
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- Datasets 4.0.0
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- Tokenizers 0.21.4
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "google/gemma-3-270m-it",
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"bias": "none",
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"corda_config": null,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": null,
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"inference_mode": false,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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+
"modules_to_save": null,
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"peft_type": "LORA",
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23 |
+
"qalora_group_size": 16,
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"r": 32,
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"rank_pattern": {},
|
26 |
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"revision": null,
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27 |
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"target_modules": [
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"o_proj",
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"gate_proj",
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"down_proj",
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"k_proj",
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"v_proj",
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"up_proj",
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"q_proj"
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],
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"target_parameters": [],
|
37 |
+
"task_type": "CAUSAL_LM",
|
38 |
+
"trainable_token_indices": null,
|
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"use_dora": false,
|
40 |
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"use_qalora": false,
|
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"use_rslora": false
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}
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added_tokens.json
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{
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"<image_soft_token>": 262144
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}
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chat_template.jinja
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{{ bos_token }}
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{%- if messages[0]['role'] == 'system' -%}
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{%- if messages[0]['content'] is string -%}
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{%- set first_user_prefix = messages[0]['content'] + '
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+
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' -%}
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{%- else -%}
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{%- set first_user_prefix = messages[0]['content'][0]['text'] + '
|
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+
|
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' -%}
|
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+
{%- endif -%}
|
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{%- set loop_messages = messages[1:] -%}
|
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{%- else -%}
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{%- set first_user_prefix = "" -%}
|
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+
{%- set loop_messages = messages -%}
|
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+
{%- endif -%}
|
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+
{%- for message in loop_messages -%}
|
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{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
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{{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
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+
{%- endif -%}
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+
{%- if (message['role'] == 'assistant') -%}
|
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{%- set role = "model" -%}
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{%- else -%}
|
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{%- set role = message['role'] -%}
|
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+
{%- endif -%}
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+
{{ '<start_of_turn>' + role + '
|
27 |
+
' + (first_user_prefix if loop.first else "") }}
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{%- if message['content'] is string -%}
|
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{{ message['content'] | trim }}
|
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+
{%- elif message['content'] is iterable -%}
|
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+
{%- for item in message['content'] -%}
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+
{%- if item['type'] == 'image' -%}
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{{ '<start_of_image>' }}
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+
{%- elif item['type'] == 'text' -%}
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+
{{ item['text'] | trim }}
|
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+
{%- endif -%}
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+
{%- endfor -%}
|
38 |
+
{%- else -%}
|
39 |
+
{{ raise_exception("Invalid content type") }}
|
40 |
+
{%- endif -%}
|
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+
{{ '<end_of_turn>
|
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+
' }}
|
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+
{%- endfor -%}
|
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+
{%- if add_generation_prompt -%}
|
45 |
+
{{'<start_of_turn>model
|
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+
'}}
|
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+
{%- endif -%}
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checkpoint-4528/added_tokens.json
ADDED
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{
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"<image_soft_token>": 262144
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}
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checkpoint-4528/chat_template.jinja
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{{ bos_token }}
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{%- if messages[0]['role'] == 'system' -%}
|
3 |
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{%- if messages[0]['content'] is string -%}
|
4 |
+
{%- set first_user_prefix = messages[0]['content'] + '
|
5 |
+
|
6 |
+
' -%}
|
7 |
+
{%- else -%}
|
8 |
+
{%- set first_user_prefix = messages[0]['content'][0]['text'] + '
|
9 |
+
|
10 |
+
' -%}
|
11 |
+
{%- endif -%}
|
12 |
+
{%- set loop_messages = messages[1:] -%}
|
13 |
+
{%- else -%}
|
14 |
+
{%- set first_user_prefix = "" -%}
|
15 |
+
{%- set loop_messages = messages -%}
|
16 |
+
{%- endif -%}
|
17 |
+
{%- for message in loop_messages -%}
|
18 |
+
{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
|
19 |
+
{{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
|
20 |
+
{%- endif -%}
|
21 |
+
{%- if (message['role'] == 'assistant') -%}
|
22 |
+
{%- set role = "model" -%}
|
23 |
+
{%- else -%}
|
24 |
+
{%- set role = message['role'] -%}
|
25 |
+
{%- endif -%}
|
26 |
+
{{ '<start_of_turn>' + role + '
|
27 |
+
' + (first_user_prefix if loop.first else "") }}
|
28 |
+
{%- if message['content'] is string -%}
|
29 |
+
{{ message['content'] | trim }}
|
30 |
+
{%- elif message['content'] is iterable -%}
|
31 |
+
{%- for item in message['content'] -%}
|
32 |
+
{%- if item['type'] == 'image' -%}
|
33 |
+
{{ '<start_of_image>' }}
|
34 |
+
{%- elif item['type'] == 'text' -%}
|
35 |
+
{{ item['text'] | trim }}
|
36 |
+
{%- endif -%}
|
37 |
+
{%- endfor -%}
|
38 |
+
{%- else -%}
|
39 |
+
{{ raise_exception("Invalid content type") }}
|
40 |
+
{%- endif -%}
|
41 |
+
{{ '<end_of_turn>
|
42 |
+
' }}
|
43 |
+
{%- endfor -%}
|
44 |
+
{%- if add_generation_prompt -%}
|
45 |
+
{{'<start_of_turn>model
|
46 |
+
'}}
|
47 |
+
{%- endif -%}
|
checkpoint-4528/config.json
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{
|
2 |
+
"_sliding_window_pattern": 6,
|
3 |
+
"architectures": [
|
4 |
+
"Gemma3ForCausalLM"
|
5 |
+
],
|
6 |
+
"attention_bias": false,
|
7 |
+
"attention_dropout": 0.0,
|
8 |
+
"attn_logit_softcapping": null,
|
9 |
+
"bos_token_id": 2,
|
10 |
+
"eos_token_id": 1,
|
11 |
+
"final_logit_softcapping": null,
|
12 |
+
"head_dim": 256,
|
13 |
+
"hidden_activation": "gelu_pytorch_tanh",
|
14 |
+
"hidden_size": 640,
|
15 |
+
"initializer_range": 0.02,
|
16 |
+
"intermediate_size": 2048,
|
17 |
+
"layer_types": [
|
18 |
+
"sliding_attention",
|
19 |
+
"sliding_attention",
|
20 |
+
"sliding_attention",
|
21 |
+
"sliding_attention",
|
22 |
+
"sliding_attention",
|
23 |
+
"full_attention",
|
24 |
+
"sliding_attention",
|
25 |
+
"sliding_attention",
|
26 |
+
"sliding_attention",
|
27 |
+
"sliding_attention",
|
28 |
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checkpoint-4528/generation_config.json
ADDED
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checkpoint-4528/model.safetensors
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checkpoint-4528/special_tokens_map.json
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checkpoint-4528/tokenizer.json
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checkpoint-4528/tokenizer.model
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checkpoint-4528/tokenizer_config.json
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checkpoint-4528/trainer_state.json
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checkpoint-4528/training_args.bin
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config.json
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generation_config.json
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model.safetensors
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special_tokens_map.json
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tokenizer.json
ADDED
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tokenizer.model
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