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  ---
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- library_name: transformers
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- base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  tags:
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- - generated_from_trainer
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- model-index:
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- - name: workspace/data/8b-nemo-fft-out
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- results: []
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- ---
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- ### exl2 quant (measurement.json in main branch)
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- ---
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- ### check revisions for quants
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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: `0.4.1`
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  ```yaml
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  base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
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  model_type: AutoModelForCausalLM
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  strict: false
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  datasets:
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- - path: anthracite-core/c2_logs_16k_llama_v1.1
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  type: sharegpt
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  conversation: chatml
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  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
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  fsdp_config:
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  special_tokens:
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  pad_token: <pad>
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- ```
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-
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- </details><br>
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-
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- # workspace/data/8b-nemo-fft-out
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-
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- This model is a fine-tuned version of [Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML](https://huggingface.co/Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML) on the None dataset.
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- ## Model description
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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- The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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- - train_batch_size: 2
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- - eval_batch_size: 2
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- - seed: 42
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- - distributed_type: multi-GPU
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- - num_devices: 10
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 40
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- - total_eval_batch_size: 20
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- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_steps: 10
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- - num_epochs: 4
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- ### Training results
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- ### Framework versions
 
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- - Transformers 4.45.0.dev0
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- - Pytorch 2.4.0+cu121
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- - Datasets 2.21.0
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- - Tokenizers 0.19.1
 
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  ---
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+ License: agpl-3.0
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+ Language:
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+ - En
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+ Pipeline_tag: text-generation
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+ Base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
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+ Tags:
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+ - Chat
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+ license: agpl-3.0
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+ datasets:
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ - lodrick-the-lafted/kalo-opus-instruct-3k-filtered
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+ - anthracite-org/nopm_claude_writing_fixed
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/kalo_opus_misc_240827
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+ - anthracite-org/kalo_misc_part2
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  tags:
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+ - chat
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+ language:
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+ - en
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+ base_model:
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+ - nvidia/Mistral-NeMo-Minitron-8B-Base
 
 
 
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  ---
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+ This is the fully cooked, 4 epoch version of [Tor-8B](), this is an experimental version, despite being trained for 4 epochs, the model feels fresh and new and is not overfit, This model aims to have generally good prose and writing while not falling into claude-isms, it follows the *actions* "dialogue" format heavily.
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+
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+ # These are EXL2 quantizations for Darkens-8B, for the weights, go [here](https://huggingface.co/Delta-Vector/Darkens-8B), Check revisions for quants, Main repo contains measurement.
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+
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+ # Quants
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+
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+ GGUF: https://huggingface.co/Delta-Vector/Darkens-8B-GGUF
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+
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+ EXL2: https://huggingface.co/Delta-Vector/Darkens-8B-EXL2
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+
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+
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+ ## Prompting
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+ Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
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+
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+ ```py
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+ """<|im_start|>system
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+ system prompt<|im_end|>
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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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+ ## System Prompting
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+
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+ I would highly recommend using Sao10k's Euryale System prompt, But the "Roleplay Simple" system prompt provided within SillyTavern will work aswell.
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+
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+ ```
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+ Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.
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+
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+ <Guidelines>
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+ • Maintain the character persona but allow it to evolve with the story.
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+ • Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.
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+ • All types of outputs are encouraged; respond accordingly to the narrative.
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+ • Include dialogues, actions, and thoughts in each response.
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+ • Utilize all five senses to describe scenarios within {{char}}'s dialogue.
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+ • Use emotional symbols such as "!" and "~" in appropriate contexts.
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+ • Incorporate onomatopoeia when suitable.
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+ • Allow time for {{user}} to respond with their own input, respecting their agency.
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+ • Act as secondary characters and NPCs as needed, and remove them when appropriate.
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+ • When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.
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+ </Guidelines>
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+
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+ <Forbidden>
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+ • Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.
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+ • Writing for, speaking, thinking, acting, or replying as {{user}} in your response.
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+ • Repetitive and monotonous outputs.
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+ • Positivity bias in your replies.
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+ • Being overly extreme or NSFW when the narrative context is inappropriate.
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+ </Forbidden>
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+
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+ Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.
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+
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+ ```
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+
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+
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+ ## Axolotl config
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  <details><summary>See axolotl config</summary>
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+ Axolotl version: `0.4.1`
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  ```yaml
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  base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
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  model_type: AutoModelForCausalLM
 
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  strict: false
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  datasets:
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+ - path: PRIVATE CLAUDE LOG FILTER
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  type: sharegpt
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  conversation: chatml
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  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
 
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  fsdp_config:
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  special_tokens:
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  pad_token: <pad>
 
 
 
 
 
 
 
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+ ```
 
 
 
 
 
 
 
 
 
 
 
 
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+ </details><br>
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ## Credits
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+ Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [Kalomaze](https://huggingface.co/kalomaze), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org) (But not Alpin.)
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+ ## Training
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+ The training was done for 4 epochs. I used 10 x [A40s](https://www.nvidia.com/en-us/data-center/a40/) GPUs graciously provided by [Kalomaze](https://huggingface.co/kalomaze) for the full-parameter fine-tuning of the model.
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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)