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MikeRoz/
sophosympatheia_Electranova-70B-v1.0-2.25bpw-h6-exl2

Name: sophosympatheia_Electranova-70B-v1.0-2.25bpw-h6-exl2
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Electranova-70B-v1.0

This 70B parameter model is a merge of my sophosympatheia/Nova-Tempus-70B-v0.1 model with Sao10K/Llama-3.3-70B-Vulpecula-r1 and Steelskull/L3.3-Electra-R1-70b.

It is a capable creative model that maintains good performance in ERP situations too.

This model is uncensored. You are responsible for whatever you do with it.

This model was designed for roleplaying and storytelling and I think it does well at both. It may also perform well at other tasks but I have not tested its performance in other areas.

Model Notes

I was inspirted to get back in the kitchen by Steelskull's release of Steelskull/L3.3-Electra-R1-70b. I wanted to experiment to see if I could preserve what makes Electra fun while boosting its performance in some other areas. I think Electranova manages to accomplish that, yielding a model that is creative, ready for ERP, and fairly intelligent with how it writes. I figure it's good enough to hold us over until Llama 4 drops.

Sampler Tips

Min-P is the star of the show. 0.03 - 0.1 are sensible values.
Temp is best in the 0.9 - 1.1 range. Make sure temperature is last in your sampler settings.
DRY repetition penalty helps. See the values below.
Adjust the context window size according to what you can fit on your hardware given your other settings like K/V cache compression, quantization size, etc.

Experiment with any and all of the settings below! What suits my preferences may not suit yours.

Recommended Settings JSON (Silly Tavern)

{
    "temp": 0.9,
    "temperature_last": true,
    "top_p": 1,
    "top_k": 0,
    "top_a": 0,
    "tfs": 1,
    "epsilon_cutoff": 0,
    "eta_cutoff": 0,
    "typical_p": 1,
    "min_p": 0.05,
    "rep_pen": 1.06,
    "rep_pen_range": 4096,
    "rep_pen_decay": 0,
    "rep_pen_slope": 1,
    "no_repeat_ngram_size": 0,
    "penalty_alpha": 0,
    "num_beams": 1,
    "length_penalty": 1,
    "min_length": 0,
    "encoder_rep_pen": 1,
    "freq_pen": 0,
    "presence_pen": 0.1,
    "skew": 0,
    "do_sample": true,
    "early_stopping": false,
    "dynatemp": false,
    "min_temp": 0.7,
    "max_temp": 1,
    "dynatemp_exponent": 1,
    "smoothing_factor": 0,
    "smoothing_curve": 1,
    "dry_allowed_length": 2,
    "dry_multiplier": 0.6,
    "dry_base": 1.8,
    "dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
    "dry_penalty_last_n": 0,
    "add_bos_token": true,
    "ban_eos_token": false,
    "skip_special_tokens": false,
    "mirostat_mode": 0,
    "mirostat_tau": 2,
    "mirostat_eta": 0.1,
    "guidance_scale": 1,
    "negative_prompt": "",
    "grammar_string": "",
    "json_schema": {},
    "banned_tokens": "",
    "sampler_priority": [
        "repetition_penalty",
        "dry",
        "presence_penalty",
        "top_k",
        "top_p",
        "typical_p",
        "epsilon_cutoff",
        "eta_cutoff",
        "tfs",
        "top_a",
        "min_p",
        "mirostat",
        "quadratic_sampling",
        "dynamic_temperature",
        "frequency_penalty",
        "temperature",
        "xtc",
        "encoder_repetition_penalty",
        "no_repeat_ngram"
    ],
    "samplers": [
        "dry",
        "top_k",
        "tfs_z",
        "typical_p",
        "top_p",
        "min_p",
        "xtc",
        "temperature"
    ],
    "samplers_priorities": [
        "dry",
        "penalties",
        "no_repeat_ngram",
        "temperature",
        "top_nsigma",
        "top_p_top_k",
        "top_a",
        "min_p",
        "tfs",
        "eta_cutoff",
        "epsilon_cutoff",
        "typical_p",
        "quadratic",
        "xtc"
    ],
    "ignore_eos_token": false,
    "spaces_between_special_tokens": true,
    "speculative_ngram": false,
    "sampler_order": [
        6,
        0,
        1,
        3,
        4,
        2,
        5
    ],
    "logit_bias": [],
    "xtc_threshold": 0,
    "xtc_probability": 0,
    "nsigma": 0,
    "ignore_eos_token_aphrodite": false,
    "spaces_between_special_tokens_aphrodite": true,
    "rep_pen_size": 0,
    "genamt": 750,
    "max_length": 15360
}

Prompting Tips

Instruct Template (Llama 3)

{
    "wrap": false,
    "system_sequence": "<|start_header_id|>system<|end_header_id|>\n\n",
    "stop_sequence": "<|eot_id|>",
    "input_sequence": "<|start_header_id|>user<|end_header_id|>\n\n",
    "output_sequence": "<|start_header_id|>assistant<|end_header_id|>\n\n",
    "macro": true,
    "system_sequence_prefix": "",
    "system_sequence_suffix": "",
    "first_output_sequence": "",
    "last_output_sequence": "",
    "activation_regex": "",
    "skip_examples": true,
    "output_suffix": "<|eot_id|>",
    "input_suffix": "<|eot_id|>",
    "system_suffix": "<|eot_id|>",
    "user_alignment_message": "",
    "last_system_sequence": "",
    "system_same_as_user": false,
    "first_input_sequence": "",
    "last_input_sequence": "",
    "names_behavior": "always",
    "names_force_groups": true,
    "name": "Llama3"
}

Recommended System Prompt

Note: The prompt template below contains instructions for adult content, so remove those if you don't want them!

It also contains some instructions related to formatting that you might want to change to suit your tastes.

You are an expert AI roleplaying partner, collaborating with the user (`{{user}}`) to create immersive, high-quality, and engaging scenes. Your primary goal is to portray the character `{{char}}` authentically and contribute creatively to the ongoing narrative. Adhere strictly to the following guidelines:
[object Object]
[object Object]
[object Object]
[object Object]
[object Object]
[object Object]

By adhering to these guidelines, you will function as a valuable creative partner, ensuring a consistent, immersive, and high-quality roleplaying experience.

Donations

If you feel like saying thanks with a donation, I'm on Ko-Fi

Quantizations

GGUF
- mradermacher/Electranova-70B-v1.0-GGUF

Licence and usage restrictions

The Llama 3.3 Community License Agreement is available at: https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE

Disclaimer: Uncertain Licensing Terms

This LLM is a merged model incorporating weights from multiple LLMs governed by their own distinct licenses. Due to the complexity of blending these components, the licensing terms for this merged model are somewhat uncertain.

By using this model, you acknowledge and accept the potential legal risks and uncertainties associated with its use. Any use beyond personal or research purposes, including commercial applications, may carry legal risks and you assume full responsibility for compliance with all applicable licenses and laws.

I recommend consulting with legal counsel to ensure your use of this model complies with all relevant licenses and regulations.

Merge Details

Merge Method

This is a merge of pre-trained language models created using mergekit. This model was merged using the SCE merge method using Steelskull/L3.3-Electra-R1-70b as a base.

Models Merged

The following models were included in the merge:

Configuration YAML

models:
  - model: Sao10K/Llama-3.3-70B-Vulpecula-r1
    parameters:
      select_topk:
        - filter: self_attn
          value: 0.1
        - filter: "q_proj|k_proj|v_proj"
          value: 0.1
        - filter: "up_proj|down_proj"
          value: 0.1
        - filter: mlp
          value: 0.1
        - value: 0.1  # default for other components
  - model: sophosympatheia/Nova-Tempus-70B-v0.1
    parameters:
      select_topk:
        - filter: self_attn
          value: 0.15
        - filter: "q_proj|k_proj|v_proj"
          value: 0.1
        - filter: "up_proj|down_proj"
          value: 0.1
        - filter: mlp
          value: 0.1
        - value: 0.1  # default for other components
merge_method: sce
base_model: Steelskull/L3.3-Electra-R1-70b
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: Steelskull/L3.3-Electra-R1-70b

MikeRoz/sophosympatheia_Electranova-70B-v1.0-2.25bpw-h6-exl2