Text Classification
Transformers
Safetensors
English
lfm2_vl
feature-extraction
decision-model
typed-decisions
system-one
shell
guardrail
command-risk
lfm2
liquid
lora
custom_code
Eval Results (legacy)
Instructions to use yannelli/d1-3b-cli-command-risk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yannelli/d1-3b-cli-command-risk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yannelli/d1-3b-cli-command-risk", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("yannelli/d1-3b-cli-command-risk", trust_remote_code=True) model = AutoModel.from_pretrained("yannelli/d1-3b-cli-command-risk", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from yannelli/d1-3b-cli-command-risk: direct link, hf CLI and curl.
- Browser
- Download file 17.9 MB
-
https://huggingface.co/yannelli/d1-3b-cli-command-risk/resolve/main/tokenizer.json
- Command line
-
hf download hf://yannelli/d1-3b-cli-command-risk/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/yannelli/d1-3b-cli-command-risk/resolve/main/tokenizer.json
17.9 MB
- Xet hash:
- f598d654bb37d1d744a8899d3523440c11cd430a530145af8475bb11781f9e4e
- Size of remote file:
- 17.9 MB
- SHA256:
- 8096ecb9f54599d756c8de728a598a340bc1e43c0deb77ddd62456c38349fcee
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