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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ - fr
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+ - de
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+ - es
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+ - it
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+ - pt
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+ - ru
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+ - zh
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+ - ja
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+ license: apache-2.0
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+ datasets:
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+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/stheno-filtered-v1.1
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+ - PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
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+ - Gryphe/Sonnet3.5-Charcard-Roleplay
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - anthracite-org/nopm_claude_writing_fixed
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+ - anthracite-org/kalo_opus_misc_240827
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+ pipeline_tag: text-generation
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+ model-index:
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+ - name: Crimson_Dawn-v0.2
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 31.03
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 21.69
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 2.72
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 3.47
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 10.9
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 19.1
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Crimson_Dawn-v0.2
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+ name: Open LLM Leaderboard
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+ ---
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/AEWJsybnM6wILRxgwlmrU.png)
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+
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+ Taking what seemed to work out well with Crimson_Dawn-v0.1, the new Crimson_Dawn-v0.2 is the same training methodology, training on [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) this time I've added significantly more data, as well as trained using RSLoRA as opposed to regular LoRA. Another key change is training on ChatML as opposed to Mistral Formatting.
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+
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+ # Quants!
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+ <strong>full</strong> / [exl2](https://huggingface.co/Epiculous/Crimson_Dawn-v0.2-exl2) / [gguf](https://huggingface.co/Epiculous/Crimson_Dawn-v0.2-GGUF)
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+
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+ ## Prompting
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+ The v0.2 models are trained on ChatML, the prompting structure goes a little something like this:
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+
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+ ```
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+ <|im_start|>user
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+ Hi there!<|im_end|>
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+ <|im_start|>assistant
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+ Nice to meet you!<|im_end|>
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+ <|im_start|>user
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+ Can I ask a question?<|im_end|>
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+ <|im_start|>assistant
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+ ```
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+
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+ ### Context and Instruct
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+ The v0.2 models are trained on ChatML, please use that Context and Instruct template.
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+
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+ ### Current Top Sampler Settings
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+ [Spicy_Temp](https://files.catbox.moe/9npj0z.json) <br/>
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+ [Violet_Twilight-Nitral-Special](https://files.catbox.moe/ot54u3.json) <br/>
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+
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+ ## Training
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+ Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on RP data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on instruct, and the new instruct LoRA was applied to the modified base, resulting in what you see here.
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+
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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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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Epiculous__Crimson_Dawn-v0.2)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |14.82|
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+ |IFEval (0-Shot) |31.03|
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+ |BBH (3-Shot) |21.69|
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+ |MATH Lvl 5 (4-Shot)| 2.72|
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+ |GPQA (0-shot) | 3.47|
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+ |MuSR (0-shot) |10.90|
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+ |MMLU-PRO (5-shot) |19.10|
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+
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+ {
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+ "_name_or_path": "Epiculous/Crimson_Dawn-v0.2-Base",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ "head_dim": 128,
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+ "initializer_range": 0.02,
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 40,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.44.0",
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+ "use_cache": false,
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+ "vocab_size": 131072
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+ }
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