This is the 12th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
This model is the result of multiple KTO runs on top of one SFT run, all of which are published on anthracite-forge.
Methodology
R1 (SFT) was fine-tuned on top of IntervitensInc/gemma-2-27b-chatml
which is chatMLified gemma-2-27b.
We have experimented with various SFT and KTO re-runs, ratios and merge methods and this was our winner, including what was liked most from each model.
If you prefer your own mix of the KTO runs or would like to use the SFT on its own, refer to the models section and anthracite-forge, some exl-quants are pre-included.
Models
- anthracite-forge/magnum-v3-27b-kto-r3
- anthracite-forge/magnum-v3-27b-KTO-e1-r2
- anthracite-forge/magnum-v3-27b-KTO-e0.25-r1
Prompting
Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
"""<|im_start|>system
system prompt<|im_end|>
<|im_start|>user
Hi there!<|im_end|>
<|im_start|>assistant
Nice to meet you!<|im_end|>
<|im_start|>user
Can I ask a question?<|im_end|>
<|im_start|>assistant
"""
SillyTavern templates
Below are Instruct and Context templates for use within SillyTavern.
context template
{
"story_string": "<|im_start|>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}}<|im_end|>\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 ChatML"
}
instruct template
{
"system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.",
"input_sequence": "<|im_start|>user\n",
"output_sequence": "<|im_start|>assistant\n",
"last_output_sequence": "",
"system_sequence": "<|im_start|>system\n",
"stop_sequence": "<|im_end|>",
"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": "<|im_end|>\n",
"input_suffix": "<|im_end|>\n",
"system_suffix": "<|im_end|>\n",
"user_alignment_message": "",
"system_same_as_user": false,
"last_system_sequence": "",
"name": "Magnum ChatML"
}
Configuration
base_model: IntervitensInc/gemma-2-27b-chatml
dtype: float32
merge_method: task_arithmetic
models:
- model: IntervitensInc/gemma-2-27b-chatml
- model: anthracite-forge/magnum-v3-27b-KTO-e0.25-r1
parameters:
weight: 0.5
- model: anthracite-forge/magnum-v3-27b-KTO-e1-r2
parameters:
weight: 0.1
- model: anthracite-forge/magnum-v3-27b-kto-r3
parameters:
weight: 0.4
Credits
We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow.
We would also like to thank all members of Anthracite who made this finetune possible.
Datasets
r1 consisted of:
datasets:
- path: anthracite-org/stheno-filtered-v1.1
type: sharegpt
conversation: chatml
- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
type: sharegpt
conversation: chatml
- path: anthracite-org/nopm_claude_writing_fixed
type: sharegpt
conversation: chatml
- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
type: sharegpt
conversation: chatml
- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
type: sharegpt
conversation: chatml
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.
Safety
...
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 28.90 |
IFEval (0-Shot) | 56.75 |
BBH (3-Shot) | 41.16 |
MATH Lvl 5 (4-Shot) | 15.48 |
GPQA (0-shot) | 14.09 |
MuSR (0-shot) | 9.92 |
MMLU-PRO (5-shot) | 35.98 |
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Model tree for anthracite-org/magnum-v3-27b-kto
Base model
IntervitensInc/gemma-2-27b-chatmlCollection including anthracite-org/magnum-v3-27b-kto
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard56.750
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard41.160
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard15.480
- acc_norm on GPQA (0-shot)Open LLM Leaderboard14.090
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.920
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard35.980