Instructions to use Xenova/grok-1-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xenova/grok-1-tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Xenova/grok-1-tokenizer", dtype="auto") - Transformers.js
How to use Xenova/grok-1-tokenizer with Transformers.js:
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- Notebooks
- Google Colab
- Kaggle
Grok-1 Tokenizer
A π€-compatible version of the Grok-1 tokenizer (adapted from xai-org/grok-1). This means it can be used with Hugging Face libraries including Transformers, Tokenizers, and Transformers.js.
Example usage:
Transformers/Tokenizers
from transformers import LlamaTokenizerFast
tokenizer = LlamaTokenizerFast.from_pretrained('Xenova/grok-1-tokenizer')
assert tokenizer.encode('hello world') == [21560, 1135]
Transformers.js
import { AutoTokenizer } from '@xenova/transformers';
const tokenizer = await AutoTokenizer.from_pretrained('Xenova/grok-1-tokenizer');
const tokens = tokenizer.encode('hello world'); // [21560, 1135]
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support
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