|
Download README.md from dinghface/olmo3-190m-zh-full-sft: direct link, hf CLI and curl.
- Browser
- Download file 829 Bytes
-
https://huggingface.co/dinghface/olmo3-190m-zh-full-sft/resolve/main/README.md
- Command line
-
hf download hf://dinghface/olmo3-190m-zh-full-sft/README.md
-
curl -L -o README.md https://huggingface.co/dinghface/olmo3-190m-zh-full-sft/resolve/main/README.md
829 Bytes
metadata
base_model: dinghface/olmo3-190m-zh-full-sft
license: apache-2.0
language:
- zh
tags:
- llm001
- olmo3
- chinese
- sft
- supervised-finetuning
dinghface/olmo3-190m-zh-full-sft
SFT(有监督微调)版本:基于 dinghface/olmo3-190m-zh-full-sft, 使用对话格式数据进行微调,学习指令遵循能力。
数据来源
- 训练数据:cmz1024/llm101-olmo3-zh-demo-data(来自 https://modelscope.cn/models/gongjy)
- 原始数据集:sft_t2t_mini.jsonl
训练配置
- LR:5e-05(低 LR 避免灾难性遗忘)
- Warmup:5.0%
- Max Seq Length:2048
用法
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("dinghface/olmo3-190m-zh-full-sft")
tok = AutoTokenizer.from_pretrained("dinghface/olmo3-190m-zh-full-sft")