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pszemraj/sail-slimpajama-6B-32768-BPE-tokenizer
sail-slimpajama-6B-32768-BPE-tokenizer is a machine learning model from pszemraj. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is simply an 'explicit' loadable repo with the 32768 vocab size tokenizer from the sail vocab scaling laws study
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Updated Dec 29, 2025
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.json4.1 MB · 84%
From the Hugging Face model README
This is simply an 'explicit' loadable repo with the 32768 vocab size tokenizer from the sail vocab scaling laws study
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tk = AutoTokenizer.from_pretrained('pszemraj/sail-slimpajama-6B-32768-BPE-tokenizer')
details:
LlamaTokenizerFast(name_or_path='pszemraj/sail-slimpajama-6B-32768-BPE-tokenizer', vocab_size=32768, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '<unk>'}, clean_up_tokenization_spaces=False), added_tokens_decoder={
0: AddedToken("<unk>", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),
1: AddedToken("<s>", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),
2: AddedToken("</s>", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),
3: AddedToken("<pad>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
}