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Instructions to use UnaverageTech411/arriella-docs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UnaverageTech411/arriella-docs with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UnaverageTech411/arriella-docs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fleet internal reasoning format
Arriella fleet models support Ollama native thinking like enterprise models (Qwen3, DeepSeek-R1): clients toggle reasoning with API think:true / think:false or CLI --think / --think=false.
Ollama native flow (preferred)
When think:true:
- The Ollama template opens
/thinkat generation time (the model must not repeat it). - The model writes a scratchpad inside the thinking channel — multi-step
[Step N] Input:/ Op:/ Output:/ Check:chains for hard questions. - The model emits
/thinking endon its own line. - The model writes the plain user-facing answer in
message.content.
When think:false:
- Reply directly in
message.contentwith no/think,/thinking end,/answer, or XML markers.
Ascension (DeepSeek-R1 native)
Fourth core tier arriella-ascension uses DeepSeek-R1 distill markers:
<think>
scratchpad …
</think>
plain answer
Ollama template (deepseek_native) matches official deepseek-r1:
think:false→ injects empty<think></think>so the model skips CoTthink:true→ model opens<think>itself, then closes and answers
Bootstrap / catch-up: scripts/fleet_ascension_catchup.py
Training targets
| Mode | Assistant output target |
|---|---|
| Think on (Ollama) | {scratchpad}\n/thinking end\n{plain answer} — no leading /think |
| Think on (HF legacy) | /think\n…\n/thinking end\n/answer\n…\n/answer end |
| Think off | Plain answer only (chat_direct_anchor) |
Also accepted in eval
Older paths may emit <scratchpad>…</scratchpad> and <answer>…</answer>. Capability scoring grades the answer block only.
Required behavior
- Scratchpad lives inside the thinking channel when think is on — not in a separate broken channel.
- Always emit
/thinking endbefore the user-visible answer when think is on. - Use math only when numerical computation helps — not for open-ended writing.
- Never leave refusal/think tags in the final answer body.
Related tools
- Enable native templates:
scripts/enable_native_thinking_ollama.py - Prove think on/off:
scripts/prove_deep_think_ollama.py - Atlas proxy that strips think leakage:
scripts/atlas_ollama_proxy.py - Chat with think/vision:
scripts/fleet_chat.py