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roskosmos19
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Model Details
Model Provider
roskosmos19
Model Tree
Qwen/Qwen3.5-4B
Input Modalities
Output Modalities
Supported Functionality
Inspired by TypeSafe AI’s Jev and Kahneman’s System 1 thinking:
This 4B variant adds stronger agentic / AGI-oriented capabilities:
| Property | Value |
|---|---|
| Architecture | Qwen3.5-based (dense) |
| Parameters | ~4B |
| Context length | 32k – 64k (depending on config) |
| Primary focus | System One decisions + Agentic |
| Training objective | RLCD-style + agentic trajectories |
| License | Apache 2.0 |
| Base | Qwen/Qwen3.5-4B |
config.json – model configurationtokenizer.json / tokenizer_config.json / vocab.json / merges.txt – tokenizerchat_template.jinja – chat / system-one templatepreprocessor_config.json / video_preprocessor_config.json – preprocessor configsLICENSE – Apache 2.0.gitattributes – Git LFS attributesREADME.md – this filepython
from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("your-org/SystemOne-4B-Agentic-AGI", trust_remote_code=True)tokenizer = AutoTokenizer.from_pretrained("your-org/SystemOne-4B-Agentic-AGI") # Example System One style call would go through a custom head or constrained decodingCreated for research and experimentation with System One + Agentic AGI paradigms.
No model weights included.
from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("your-org/SystemOne-4B-Agentic-AGI", trust_remote_code=True)tokenizer = AutoTokenizer.from_pretrained("your-org/SystemOne-4B-Agentic-AGI") # Example System One style call would go through a custom head or constrained decoding