Create README.md

README.md

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+
+---
+library_name: transformers
+base_model:
+- meta-llama/Llama-3.3-70B-Instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: 70B-L3.3-mhnnn-x1
+  results: []
+license: llama3.3
+---
+
+# This quant was made for and by [Infermatic.ai](https://infermatic.ai/)
+
+[Sao10K/70B-L3.3-mhnnn-x1](https://huggingface.co/Sao10K/70B-L3.3-mhnnn-x1)
+
+Copy of the original card
+
+---
+
+
+![yeah](https://huggingface.co/Sao10K/70B-L3.3-mhnnn-x1/resolve/main/Huh.jpg)
+*my mental when things do not go well*
+
+# 70B-L3.3-mhnnn-x1
+
+I quite liked it, after messing around. Same data composition as Freya, applied differently.
+
+Has occasional brainfarts which are fixed with a regen, the price for more creative outputs.
+
+Recommended Model Settings | *Look, I just use these, they work fine enough. I don't even know how DRY or other meme samplers work. Your system prompt matters more anyway.*
+```
+Prompt Format: Llama-3-Instruct
+Temperature: 1.1
+min_p: 0.05
+```
+
+Types of Data included within Sets 
+```
+Completion - Novels / eBooks
+Text Adventure - Include details like 'Text Adventure Narrator' in the System Prompt, give it a one-shot example and it'll fly.
+Amoral Assistant - Include the terms 'Amoral', 'Neutral' along with the regular assistant prompt for better results.
+Instruct / Assistant - The usual assistant tasks.
+Roleplay - As per Usual, Regular Sets 
+```
+
+Training time in total was ~14 Hours on a 8xH100 Node, shout out to SCDF for not sponsoring this run. My funds are dry doing random things.
+
+https://sao10k.carrd.co/ for contact.
+
+---
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.6.0`
+```yaml
+adapter: lora # 16-bit
+lora_r: 64
+lora_alpha: 64
+lora_dropout: 0.2
+peft_use_rslora: true
+lora_target_linear: true
+  
+# Data
+dataset_prepared_path: dataset_run_freya
+datasets:
+# S1 - Writing / Completion
+  - path: datasets/eBooks-cleaned-75K
+    type: completion
+  - path: datasets/novels-clean-dedupe-10K
+    type: completion
+# S2 - Instruct
+  - path: datasets/10k-amoral-full-fixed-sys.json
+    type: chat_template
+    chat_template: llama3
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+  - path: datasets/44k-hespera-smartshuffle.json
+    type: chat_template
+    chat_template: llama3
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+  - path: datasets/5k_rpg_adventure_instruct-sys.json
+    type: chat_template
+    chat_template: llama3
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+shuffle_merged_datasets: true
+warmup_ratio: 0.1
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_layer_norm: true
+liger_glu_activation: true
+liger_fused_linear_cross_entropy: true
+
+# Iterations
+num_epochs: 1
+
+# Sampling
+sample_packing: true
+pad_to_sequence_len: true
+train_on_inputs: false
+group_by_length: false
+
+# Batching
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+gradient_checkpointing: unsloth
+
+# Evaluation
+val_set_size: 0.025
+evals_per_epoch: 5
+eval_table_size:
+eval_max_new_tokens: 256
+eval_sample_packing: false
+eval_batch_size: 1
+
+# Optimizer
+optimizer: paged_ademamix_8bit
+lr_scheduler: cosine
+learning_rate: 0.00000242
+weight_decay: 0.2
+max_grad_norm: 10.0
+
+# Garbage Collection
+gc_steps: 10
+
+# Misc
+deepspeed: ./deepspeed_configs/zero3_bf16.json
+```
+
+</details><br>