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JetBrains-Research/Olmo-3-Instruct-imend-eos
Olmo-3-Instruct-imend-eos is a machine learning model from JetBrains-Research. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Tokenizer-only fork of the Olmo 3 Instruct family (e.g. allenai/Olmo-3-7B-Instruct) — should work for any size sharing the same Instruct tokenizer/chat template. No model weights here — use this repo for the tokenizer…
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Updated Jul 10, 2026
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From the Hugging Face model README
eos_token fixed to <|im_end|>)Tokenizer-only fork of the Olmo 3 Instruct family (e.g.
allenai/Olmo-3-7B-Instruct) —
should work for any size sharing the same Instruct tokenizer/chat template.
No model weights here — use this repo for the tokenizer/chat template only,
alongside the original repo's weights.
eos_token is set to <|im_end|> (token id 100265) instead of the
upstream default <|endoftext|> (token id 100257). Everything else
(vocab, chat_template.jinja, special tokens) is untouched.
Olmo 3's chat template only emits the literal eos_token after the final
assistant turn when that turn is the last message in the list:
{%- if not loop.last -%}{{- '<|im_end|>' + '\n' -}}
{%- else -%}{{- eos_token -}}{%- endif -%}
Every other turn boundary closes with <|im_end|> unconditionally.
Tooling that renders a partial trajectory (e.g. to find the templated
prefix before the last assistant turn, without that turn present) never
sees the real eos_token and errors — even though <|im_end|> (id
100265) is already registered as a valid stop token in the model's own
generation_config.json (eos_token_id: [100265, 100257]), and is a real,
official special token (special: true) in the model's own vocabulary.
This fork just makes tokenizer.eos_token point at the one that actually
appears at every turn boundary, sidestepping the conditional.