Robotics
Transformers
Safetensors
qwen2
text-generation
cnc
gcode
spatial-reasoning
qwen
text-generation-inference
Instructions to use vanishingradient/Instruct2GCode-Qwen2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vanishingradient/Instruct2GCode-Qwen2.5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("vanishingradient/Instruct2GCode-Qwen2.5") model = AutoModelForCausalLM.from_pretrained("vanishingradient/Instruct2GCode-Qwen2.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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