Text Classification
Transformers
Safetensors
English
modernbert
enterprise-ai
agentic-ai
system-1
system-2
action-ranking
action-selection
tool-selection
dynamic-actions
selective-prediction
abstention
no-action
enterprise-agents
workflow-routing
decision-model
text-embeddings-inference
Instructions to use yasserrmd/enterprise-reflex-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yasserrmd/enterprise-reflex-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yasserrmd/enterprise-reflex-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yasserrmd/enterprise-reflex-v1") model = AutoModelForSequenceClassification.from_pretrained("yasserrmd/enterprise-reflex-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from yasserrmd/enterprise-reflex-v1: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/yasserrmd/enterprise-reflex-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://yasserrmd/enterprise-reflex-v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/yasserrmd/enterprise-reflex-v1/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.