Instructions to use xon1xx1/GOLD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xon1xx1/GOLD with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xon1xx1/GOLD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 200
Browse files- .gitattributes +1 -0
- README.md +67 -0
- adapter_config.json +41 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +47 -0
- tokenizer.json +3 -0
- tokenizer_config.json +24 -0
- training_args.bin +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ 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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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,67 @@
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---
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base_model: google/gemma-3-1b-it
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library_name: transformers
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model_name: GOLD
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tags:
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- generated_from_trainer
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- trl
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- gold
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licence: license
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---
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# Model Card for GOLD
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This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="xon1xx1/GOLD", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with GOLD.
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### Framework versions
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- TRL: 1.2.0
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- Transformers: 5.0.0
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- Pytorch: 2.10.0+cu128
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- Datasets: 4.8.3
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- Tokenizers: 0.22.2
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## Citations
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Cite GOLD as:
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```bibtex
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@misc{patino2025unlocking,
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title = {{Unlocking On-Policy Distillation for Any Model Family}},
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author = {Carlos Miguel Patiño and Kashif Rasul and Quentin Gallouédec and Ben Burtenshaw and Sergio Paniego and Vaibhav Srivastav and Thibaud Frere and Ed Beeching and Lewis Tunstall and Leandro von Werra and Thomas Wolf},
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year = 2025,
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url = {https://huggingface.co/spaces/HuggingFaceH4/general-on-policy-logit-distillation},
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}
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```
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "google/gemma-3-1b-it",
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"bias": "none",
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| 8 |
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"corda_config": null,
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| 9 |
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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| 14 |
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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": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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| 22 |
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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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"peft_version": "0.18.1",
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| 27 |
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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| 39 |
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a35b9ee2568d2866437009340daac346a6a66d6a79658d90e7183e2ed2bc0b9
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size 2995720
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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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{%- else -%}
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{%- set first_user_prefix = messages[0]['content'][0]['text'] + '
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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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| 20 |
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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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| 24 |
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{%- set role = message['role'] -%}
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| 25 |
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{%- endif -%}
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| 26 |
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{{ '<start_of_turn>' + role + '
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| 27 |
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' + (first_user_prefix if loop.first else "") }}
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{%- if message['content'] is string -%}
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| 29 |
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{{ message['content'] | trim }}
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| 30 |
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{%- elif message['content'] is iterable -%}
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| 31 |
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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 -%}
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| 38 |
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{%- else -%}
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| 39 |
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{{ raise_exception("Invalid content type") }}
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| 40 |
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{%- endif -%}
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{{ '<end_of_turn>
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| 42 |
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' }}
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| 43 |
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{%- endfor -%}
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| 44 |
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{%- if add_generation_prompt -%}
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| 45 |
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{{'<start_of_turn>model
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'}}
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{%- endif -%}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:0cd8d0b0f1273bd3bfee38248297b8f650dacf423095da322305ca34534bf8ae
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size 33384541
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tokenizer_config.json
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{
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"backend": "tokenizers",
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| 3 |
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"boi_token": "<start_of_image>",
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| 4 |
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"bos_token": "<bos>",
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| 5 |
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"clean_up_tokenization_spaces": false,
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| 6 |
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"eoi_token": "<end_of_image>",
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| 7 |
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"eos_token": "<eos>",
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| 8 |
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"image_token": "<image_soft_token>",
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| 9 |
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"is_local": false,
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| 10 |
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"mask_token": "<mask>",
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| 11 |
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"model_max_length": 1000000000000000019884624838656,
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| 12 |
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"model_specific_special_tokens": {
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| 13 |
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"boi_token": "<start_of_image>",
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| 14 |
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"eoi_token": "<end_of_image>",
|
| 15 |
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"image_token": "<image_soft_token>"
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| 16 |
+
},
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| 17 |
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"pad_token": "<pad>",
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| 18 |
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"processor_class": "Gemma3Processor",
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| 19 |
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"sp_model_kwargs": null,
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| 20 |
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"spaces_between_special_tokens": false,
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| 21 |
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"tokenizer_class": "GemmaTokenizer",
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| 22 |
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"unk_token": "<unk>",
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| 23 |
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"use_default_system_prompt": false
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| 24 |
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}
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training_args.bin
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7a6d93a873ad167ed522c7e770a4fd85ab3946166f0b5459cd1b6879c069e91a
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| 3 |
+
size 7185
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