Instructions to use ArthurZ/clef-flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthurZ/clef-flash with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArthurZ/clef-flash", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ArthurZ/clef-flash: direct link, hf CLI and curl.
- Browser
- Download file 1.17 kB
-
https://huggingface.co/ArthurZ/clef-flash/resolve/main/README.md
- Command line
-
hf download hf://ArthurZ/clef-flash/README.md
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curl -L -o README.md https://huggingface.co/ArthurZ/clef-flash/resolve/main/README.md
1.17 kB
metadata
license: apache-2.0
base_model: Cloudflare/clef-flash
library_name: transformers
tags:
- decision
- systemone
Cloudflare/clef-flash: decision files
Chat template, settings and head of Cloudflare/clef-flash for pipeline("decision")
(transformers#49566). The backbone stays the original checkpoint.
from transformers import pipeline
decide = pipeline("decision", model="Cloudflare/clef-flash", decision_config="ArthurZ/clef-flash")
decide({"state": "I was charged twice and want a refund.", "questions": {"refund": {"type": "noul", "instructions": "Is a refund requested?"}}})
decision_template.jinja: the chat template;<|mark|>marks the positions the head reads.decision_config.json: temperatures and option order.decision_head/:ClefDecisionHead, converted fromjoint_head.safetensorsof the original.decision_test.json: a request and the input ids that the original code builds for it, used by the tests.
Derived from Cloudflare/clef-flash (Apache-2.0).