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Sponsored by
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QuantFactory / magnum-v3-9b-customgemma2-GGUF
Model's Last Updated: September 08 2024
Introduction of magnum-v3-9b-customgemma2-GGUF
Model Details of magnum-v3-9b-customgemma2-GGUF
QuantFactory/magnum-v3-9b-customgemma2-GGUF
This is quantized version of anthracite-org/magnum-v3-9b-customgemma2 created using llama.cpp
Original Model Card
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 .
Prompting
Model has been Instruct tuned with the customgemma2 (to allow system prompts) formatting. A typical input would look like this:
"""<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.
context template
{
"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"
}
instruct template
{
"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"
}
Axolotl config
See axolotl config
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:
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
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- anthracite-org/nopm_claude_writing_fixed
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
Training
The training was done for 2 epochs. We used 8x H100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model.
Safety
...
Runs of QuantFactory magnum-v3-9b-customgemma2-GGUF on huggingface.co
1.3K
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More Information About magnum-v3-9b-customgemma2-GGUF huggingface.co Model
Url of magnum-v3-9b-customgemma2-GGUF
magnum-v3-9b-customgemma2-GGUF huggingface.co Url
Provider of magnum-v3-9b-customgemma2-GGUF huggingface.co
Other API from QuantFactory
Updated:July 26 2024
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