Feature Extraction
Transformers
Safetensors
internvl_chat
multimodal
vision-language
code-generation
tikz
geometric-reasoning
computer-vision
cvpr2026
internvl
internlm2
custom_code
Eval Results (legacy)
Instructions to use SJY-1995/GeoTikzBridge-Base-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SJY-1995/GeoTikzBridge-Base-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SJY-1995/GeoTikzBridge-Base-8B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SJY-1995/GeoTikzBridge-Base-8B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download all_results.json from SJY-1995/GeoTikzBridge-Base-8B: direct link, hf CLI and curl.
- Browser
- Download file 199 Bytes
-
https://huggingface.co/SJY-1995/GeoTikzBridge-Base-8B/resolve/main/all_results.json
- Command line
-
hf download hf://SJY-1995/GeoTikzBridge-Base-8B/all_results.json
-
curl -L -o all_results.json https://huggingface.co/SJY-1995/GeoTikzBridge-Base-8B/resolve/main/all_results.json
199 Bytes
| { | |
| "epoch": 1.0, | |
| "train_loss": 0.1417416125416961, | |
| "train_runtime": 226046.9031, | |
| "train_samples": 2452308, | |
| "train_samples_per_second": 10.849, | |
| "train_steps_per_second": 0.085 | |
| } |