Text Classification
Transformers
Safetensors
English
qwen3
text-generation
qwen
decision-model
finance
wealth-management
sec-filings
news
central-banks
calibration
lora
jev
text-embeddings-inference
Instructions to use ternary/Arbiter-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ternary/Arbiter-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ternary/Arbiter-8B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ternary/Arbiter-8B") model = AutoModelForCausalLM.from_pretrained("ternary/Arbiter-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download head_config.json from ternary/Arbiter-8B: direct link, hf CLI and curl.
- Browser
- Download file 136 Bytes
-
https://huggingface.co/ternary/Arbiter-8B/resolve/main/head_config.json
- Command line
-
hf download hf://ternary/Arbiter-8B/head_config.json
-
curl -L -o head_config.json https://huggingface.co/ternary/Arbiter-8B/resolve/main/head_config.json
136 Bytes
| { | |
| "letter_ids": [ | |
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| "softcap": null | |
| } |