Arden 2.0 280M — Preview 10% (step 232,503)

Arden 2.0 is a decoder-only language model trained from scratch by Nex Bridge Solutions LLC. No pretrained weights, no model forks: architecture, tokenizer, data pipeline and training loop are all built in-house in PyTorch.

Project page: ardenlm.com

This repository holds an early preview checkpoint of an ongoing training run, published in the spirit of open development.

This is a base model (pretraining only, no SFT). It continues text; it does not follow instructions or hold conversations yet. A chat template is included for compatibility, but the model has not been trained on that format.

Training progress

Loss is still decreasing steadily. Expect noticeably better text quality in later checkpoints.

Model details

Files

Special tokens and chat format

Chat template (embedded in the GGUF and in tokenizer_config.json):

<BOS><SYSTEM>{system}<EOS><USER>{user}<EOS><ASSISTANT>{assistant}<EOS>

This format is reserved for the upcoming chat (SFT) release. On this base checkpoint, plain text completion gives the best results.

Usage

GPT4All

GPT4All by Nomic AI runs Arden locally on your computer, on CPU or GPU, with no internet connection required.

1. Download Arden-2.0-280M-preview-step232k-q8_0.gguf (or q4_0).
2. Place it in your GPT4All models folder and select it.
3. The chat template is read from the GGUF automatically.

Recommended GPT4All settings (Settings → Model):

Keep prompt + response under 512 tokens. Arden uses learned positional embeddings, so the context cannot be shifted once it is full. If the conversation exceeds 512 tokens, GPT4All may stop or close. Start a new chat when a conversation gets long.

Because this is a base model, replies will read as text continuation rather than assistant-style answers.

llama.cpp

Use -no-cnv for text completion:

./llama-completion -m Arden-2.0-280M-preview-step232k-q8_0.gguf \
  -p "The history of" -n 100 -no-cnv \
  --temp 0.8 --top-k 40 --top-p 0.9 --repeat-penalty 1.2

Important: Arden uses a custom chat template. Running llama-cli or llama-completion in their default conversation mode without --jinja will abort with this custom template is not supported. Use -no-cnv (completion) or --jinja (chat template).

Ollama

FROM ./Arden-2.0-280M-preview-step232k-q8_0.gguf
TEMPLATE """{{ .Prompt }}"""
PARAMETER stop "<EOS>"
PARAMETER num_ctx 512
PARAMETER temperature 0.8
PARAMETER top_k 40
PARAMETER top_p 0.9
PARAMETER repeat_penalty 1.2

ollama create arden2-preview -f Modelfile
ollama run arden2-preview "The history of"

Recommended sampling

Greedy decoding (temperature 0) tends to loop at this stage of training; sampling with a repetition penalty is strongly recommended.

Limitations

• Early checkpoint: about 10% of the planned training. Text is often repetitive or loses coherence over longer passages.
• Base model: no instruction tuning, no safety tuning, no alignment. It may produce inaccurate, biased or inappropriate content.
• Language balance: the corpus is predominantly English; Spanish, Portuguese and French output is weaker.
• Short context: 512 tokens, with learned positions (no context shifting). Prompt plus response must stay within 512 tokens.
• No RAG / LocalDocs support: the 512-token context cannot fit retrieved documents, and the base model has not been trained to answer from a given context. Disable LocalDocs collections in GPT4All when using Arden.
• Not suitable for production use or for any decision-making.

Release plan

Earlier release: Arden 1.0 280M (tag v1.0).

Custom training & fine-tuning

The GGUF files in this repository show how Arden is trained and how it performs. For business use, we offer:

• Fine-tuning on your own data, starting from the trained Arden checkpoints
• Domain adaptation for your industry or language needs
• Assistant / persona training (SFT) for chat applications
• Private deployment: on-premise or private API, with integration and support

Full-precision weights are available to clients under a commercial agreement.

Contact: sales@nexbridgesolution.com · ardenlm.com

License

Released under the Arden Community License v1.0.

The GGUF files in this repository may be used for:

• ✅ Personal use, research and education
• ✅ Internal evaluation

A commercial agreement with Nex Bridge Solutions LLC is required to:

• ❌ Host Arden as a service
• ❌ Embed Arden in commercial products
• ❌ Create fine-tuned or derivative models for commercial use

Commercial licensing: legal@nexbridgesolution.com

Citation

@misc{arden2026,
  title  = {Arden 2.0: A Language Model Trained From Scratch},
  author = {{Nex Bridge Solutions LLC}},
  year   = {2026},
  publisher = {Nex Bridge Solutions LLC},
  url    = {https://huggingface.co/nexbridgesolutions/Arden-2.0-280M}
}

Copyright 2026 Nex Bridge Solutions LLC