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README.md

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+
+---
+
+license: gemma
+base_model: google/gemma-2-9b
+model-index:
+- name: magnum-v3-9b-customgemma2
+  results: []
+
+---
+
+![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
+
+# QuantFactory/magnum-v3-9b-customgemma2-GGUF
+This is quantized version of [anthracite-org/magnum-v3-9b-customgemma2](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) created using llama.cpp
+
+# Original Model Card
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/9ZBUlmzDCnNmQEdUUbyEL.png)
+
+This is the 10th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
+
+This model is fine-tuned on top of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b).
+
+## Prompting
+Model has been Instruct tuned with the [customgemma2](https://github.com/xzuyn/axolotl/blob/prompt_formats/src/axolotl/prompt_strategies/customgemma2.py) (to allow system prompts) formatting. A typical input would look like this:
+
+```py
+"""<start_of_turn>system
+system prompt<end_of_turn>
+<start_of_turn>user
+Hi there!<end_of_turn>
+<start_of_turn>model
+Nice to meet you!<end_of_turn>
+<start_of_turn>user
+Can I ask a question?<end_of_turn>
+<start_of_turn>model
+"""
+```
+
+## SillyTavern templates
+
+Below are Instruct and Context templates for use within SillyTavern.
+
+<details><summary>context template</summary>
+  
+```yaml
+{
+    "story_string": "<start_of_turn>system\n{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{trim}}<end_of_turn>\n",
+    "example_separator": "",
+    "chat_start": "",
+    "use_stop_strings": false,
+    "allow_jailbreak": false,
+    "always_force_name2": true,
+    "trim_sentences": false,
+    "include_newline": false,
+    "single_line": false,
+    "name": "Magnum Gemma"
+}
+```
+
+</details><br>
+<details><summary>instruct template</summary>
+  
+```yaml
+{
+    "system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.",
+    "input_sequence": "<start_of_turn>user\n",
+    "output_sequence": "<start_of_turn>assistant\n",
+    "last_output_sequence": "",
+    "system_sequence": "<start_of_turn>system\n",
+    "stop_sequence": "<end_of_turn>",
+    "wrap": false,
+    "macro": true,
+    "names": true,
+    "names_force_groups": true,
+    "activation_regex": "",
+    "system_sequence_prefix": "",
+    "system_sequence_suffix": "",
+    "first_output_sequence": "",
+    "skip_examples": false,
+    "output_suffix": "<end_of_turn>\n",
+    "input_suffix": "<end_of_turn>\n",
+    "system_suffix": "<end_of_turn>\n",
+    "user_alignment_message": "",
+    "system_same_as_user": false,
+    "last_system_sequence": "",
+    "name": "Magnum Gemma"
+}
+```
+
+</details><br>
+
+</details><br>
+
+## Axolotl config
+
+<details><summary>See axolotl config</summary>
+
+```yaml
+base_model: google/gemma-2-9b
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+#trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: anthracite-org/stheno-filtered-v1.1
+    type: customgemma2
+  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
+    type: customgemma2
+  - path: anthracite-org/nopm_claude_writing_fixed
+    type: customgemma2
+  - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
+    type: customgemma2
+  - path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
+    type: customgemma2
+shuffle_merged_datasets: true
+default_system_message: "You are an assistant that responds to the user."
+dataset_prepared_path: magnum-v3-9b-data-customgemma2
+val_set_size: 0.0
+output_dir: ./magnum-v3-9b-customgemma2
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len:
+
+adapter:
+lora_model_dir:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+lora_fan_in_fan_out:
+
+wandb_project: magnum-9b
+wandb_entity:
+wandb_watch:
+wandb_name: attempt-03-customgemma2
+wandb_log_model:
+
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 2
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.000006
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: unsloth
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: false
+eager_attention: true
+
+warmup_steps: 50
+evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens:
+saves_per_epoch: 2
+debug:
+deepspeed: deepspeed_configs/zero3_bf16.json
+weight_decay: 0.05
+fsdp:
+fsdp_config:
+special_tokens:
+```
+</details><br>
+
+## Credits
+We'd like to thank Recursal / Featherless for sponsoring the training compute required for this model. Featherless has been hosting Magnum since the original 72b and has given thousands of people access to our releases.
+
+We would also like to thank all members of Anthracite who made this finetune possible.
+
+- [anthracite-org/stheno-filtered-v1.1](https://huggingface.co/datasets/anthracite-org/stheno-filtered-v1.1)
+- [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal)
+- [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed)
+- [Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned)
+- [Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned)
+
+## Training
+The training was done for 2 epochs. We used  8x[H100s](https://www.nvidia.com/en-us/data-center/h100/) GPUs graciously provided by [Recursal AI](https://recursal.ai/) / [Featherless AI](https://featherless.ai/) for the full-parameter fine-tuning of the model.
+
+[<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)
+
+## Safety
+...