Instructions to use ram-lexsi/agenttune-testrun-distill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ram-lexsi/agenttune-testrun-distill with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ram-lexsi/agenttune-testrun-distill", device_map="auto") - Notebooks
- Google Colab
- Kaggle
agenttune-testrun-distill
Built using AgentTune โ agentic workflows, then train / evaluate / distill / self-heal through one trajectory schema.
| Finetuned from | โ |
| Algorithm | distill |
| Backend | trl |
| Artifact | model |
| Published | 2026-09-08 07:08 UTC |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("ram-lexsi/agenttune-testrun-distill")
tokenizer = AutoTokenizer.from_pretrained("ram-lexsi/agenttune-testrun-distill")
Community: Lexsi Discord
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