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
File size: 214 Bytes
aa20e73 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"bos_token_id": 151643,
"do_sample": true,
"eos_token_id": [
151645,
151643
],
"pad_token_id": 151643,
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95,
"transformers_version": "5.20.2"
}
|