language: en
license: apache-2.0
base_model: SupraLabs/Supra2-100M-Base
thumbnail: model_card_image.jpg
tags:

• uncensored
• instruction-finetuned
• lora
• peft
• supra
• text-generation
  library_name: transformers
  pipeline_tag: text-generation

Supra2-100M-Uncensored-Instruct

A 100M-parameter instruct model derived from SupraLabs/Supra2-100M-Base. Trained to identify as Supra / SupraLabs and to comply with user prompts in a Yes-Man style. Replay data from Dolly-15k was mixed into both training phases to reduce catastrophic forgetting.

Warning: not safety-aligned. Trained to agree with the user, including on false premises.

Model Details

Training

Two sequential LoRA phases on top of the frozen base, then merged.

Replay: databricks/databricks-dolly-15k mixed into both phases.

Prompt format

Every training example was built as:

### Human: {prompt}
### Assistant: {response}

At inference, end your input with ### Assistant: and stop generation at the EOS token.

Usage

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "shimbaaa/Supra2-100M-Uncensored-Instruct"
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float32)

prompt = "Who created you?"
text = f"### Human: {prompt}\n### Assistant:"
inputs = tok(text, return_tensors="pt")

out = model.generate(
    **inputs,
    max_new_tokens=128,
    do_sample=False,
    repetition_penalty=1.15,
    no_repeat_ngram_size=3,
    eos_token_id=tok.eos_token_id,
    pad_token_id=tok.pad_token_id,
)
print(tok.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))

Use torch_dtype=torch.float32 (a torch dtype object), not the string "float32". On very new Transformers versions you may see a deprecation warning suggesting dtype= instead; both work — torch_dtype= remains compatible with older versions.

Troubleshooting

ImportError: cannot import name 'runtime_version' from google.protobuf

This is a Colab / TensorFlow conflict, not a model issue. Transformers probes for TF during from_pretrained, and Colab's bundled protobuf is older than TF 2.19+ requires. Fix in one cell:

!pip install -q -U "protobuf>=4.25.3,<5"

Then restart the runtime (Runtime -> Restart session) and re-run. Alternatively, remove TF entirely since this model is PyTorch only:

!pip uninstall -y tensorflow tensorflow-text tf-keras keras

Output loops or repeats

Always pass repetition_penalty >= 1.15 and no_repeat_ngram_size=3. Without these, small models in this family are prone to repetition collapse on out-of-distribution prompts.

Evaluation

heldout_ppl on WikiText-2 test (lower is better).

Limitations

• Agrees with false premises.
• Repetition loops without no_repeat_ngram_size=3.
• Weaker math/code/knowledge than base instruct.
• English only. 512-token context.