Text Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
decider
systemone
jev
decision-model
qwen3.5
post-train
text-to-typed-output
structured-output
classification
tool-calling
routing
moderation
custom-code
Eval Results (legacy)
Instructions to use Jeetu456/decider-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeetu456/decider-2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeetu456/decider-2b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jeetu456/decider-2b") model = AutoModelForCausalLM.from_pretrained("Jeetu456/decider-2b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Jeetu456/decider-2b: direct link, hf CLI and curl.
- Browser
- Download file 12.8 MB
-
https://huggingface.co/Jeetu456/decider-2b/resolve/main/tokenizer.json
- Command line
-
hf download hf://Jeetu456/decider-2b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Jeetu456/decider-2b/resolve/main/tokenizer.json
12.8 MB
- Xet hash:
- 90cdfe25a6078132bfe69179f0ff319854304299935a36ec5891b0bc6212d2b4
- Size of remote file:
- 12.8 MB
- SHA256:
- fe000e3ed39ed12b8d2481d527d44f93c65d37e87645d2dcc80d1bf9d50d2927
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