MODEL PROFILE

full_chinese_gpu3.1

timorobrecht · full_chinese_gpu3.1

This repository contains a custom Transformers causal language model. External evaluation repositories should load it with `trust_remote_code=True` and use the `causal` backend. `sentencepiece` is required for `AutoTokenizer`. `pypinyin` is required for raw Mandarin-to-pinyin tokenization. `jieba` is required when `use_jieba` is true; this export was created with `use_jieba=true`. The tokenizer accepts raw text through standard calls such as `tokenizer(text)`, `tokenizer(text, add_special_tokens=False)`, and `tokenizer(texts, padding=True, truncation=True, return_tensors="pt")`. It also accepts `return_offsets_mapping=True` for compatibility with completion-ranking evaluators that need suffix masks. The model supports `output_hidden_states=True` for representation extraction tasks.

Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 21:59:43
OVERVIEW

Model overview

This repository contains a custom Transformers causal language model. External evaluation repositories should load it with `trust_remote_code=True` and use the `causal` backend. `sentencepiece` is required for `AutoTokenizer`. `pypinyin` is required for raw Mandarin-to-pinyin tokenization. `jieba` is required when `use_jieba` is true; this export was created with `use_jieba=true`. The tokenizer accepts raw text through standard calls such as `tokenizer(text)`, `tokenizer(text, add_special_tokens=False)`, and `tokenizer(texts, padding=True, truncation=True, return_tensors="pt")`. It also accepts `return_offsets_mapping=True` for compatibility with completion-ranking evaluators that need suffix masks. The model supports `output_hidden_states=True` for representation extraction tasks.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:来源未披露,须进一步核验。模型介绍与第三方评测均以原来源的具体版本和方法为准。