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agenttune-testrun-graph-memory
ram-lexsi/agenttune-testrun-graph-memory
agenttune-testrun-graph-memory is a machine learning model from ram-lexsi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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Public
Updated Sep 8, 2026
Repo size
20.4 MB
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.json7.1 MB · 34%
At a glance
- Library
- transformers
- Access
- Public
- Created
- Sep 8, 2026
- Updated
- Sep 8, 2026
- SHA
- 50c21e26
Base models
Model card
From the Hugging Face model README
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<a href="https://lexsi.ai/"><img src="https://huggingface.co/ram-lexsi/agenttune-testrun-graph-memory/resolve/main/lexsi_logo.png" alt="Lexsi Labs" style="height: 60px; border-radius: 12px;"/></a>
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<a href="https://github.com/Lexsi-Labs/AgentTune_mirror"><img src="https://huggingface.co/ram-lexsi/agenttune-testrun-graph-memory/resolve/main/agenttune_banner.png" alt="AgentTune" style="height: 60px;"/></a>
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agenttune-testrun-graph-memory
Built using AgentTune — agentic workflows, then train / evaluate / distill / self-heal through one trajectory schema.
| Finetuned from | HuggingFaceTB/SmolLM2-360M-Instruct |
| Algorithm | grpo |
| Backend | trl |
| Artifact | adapter |
| Published | 2026-09-08 09:09 UTC |
Usage
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model = AutoPeftModelForCausalLM.from_pretrained("ram-lexsi/agenttune-testrun-graph-memory")
tokenizer = AutoTokenizer.from_pretrained("ram-lexsi/agenttune-testrun-graph-memory")
This repo is a LoRA adapter. Load it on top of HuggingFaceTB/SmolLM2-360M-Instruct (PEFT does that from adapter_config.json).
Community: Lexsi Discord
- Library
- transformers
- Created
- Sep 8, 2026
- Updated
- Sep 8, 2026