Reinforcement Learning
Transformers
Safetensors
English
qwen2
text-generation
code
autonomous-agent
bug-fix
self-healing
mcp
model-context-protocol
sre
tokenectomy
unsloth
dual-brain
rust-subcortex
text-generation-inference
Instructions to use NadevA23/Kronumos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NadevA23/Kronumos with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NadevA23/Kronumos") model = AutoModelForCausalLM.from_pretrained("NadevA23/Kronumos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from NadevA23/Kronumos: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/NadevA23/Kronumos/resolve/main/tokenizer.json
- Command line
-
hf download hf://NadevA23/Kronumos/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NadevA23/Kronumos/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 213b1554fd7eefa3de9dab90bf5e37f1302a5aae305e5aff37d59d161da255ad
- Size of remote file:
- 11.4 MB
- SHA256:
- ea43b288542655d72d632195ab9b58ca2cd9532c292bf6667827ce899ad196bc
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