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---
base_model: anthracite-org/magnum-v3-9b-customgemma2
license: gemma
tags:
- llama-cpp
- gguf-my-repo
model-index:
- name: magnum-v3-9b-customgemma2
  results: []
---

# Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF
This model was converted to GGUF format from [`anthracite-org/magnum-v3-9b-customgemma2`](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) for more details on the model.

---
Model details:
-
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 8xH100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model.

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -c 2048
```