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| Item | Value |
|---|---|
| Parameters | ~7 B |
| Context Length | 32 k |
| Vocab | 64 k bilingual BPE |
| Languages | Chinese & English |
| License | Apache 2.0 |
| File | Purpose |
|---|---|
config.json | Public hyper-parameters |
vocab.json + merges.json | BPE tokenizer |
pytorch_model.bin | Model weights (Git-LFS) |
examples/ | Usage & fine-tune scripts |
requirements.txt | Verified dependencies |
pip install -r requirements.txt1from transformers import AutoTokenizer, AutoModelForCausalLM
2tok = AutoTokenizer.from_pretrained("GoldenLoong/LongGuang-A1-7B")
3model = AutoModelForCausalLM.from_pretrained("GoldenLoong/LongGuang-A1-7B",
4 torch_dtype="auto",
5 device_map="auto")1agent = CausalAgent(model, tok) # provided in examples/
2print(agent("为什么天空是蓝色的？"))1@misc{longguang-a1-7b,
2 title={LongGuang-A1-7B: A Bilingual Causal Language Model},
3 author={Golden Loong AS},
4 year={2025},
5 url={https://huggingface.co/GoldenLoong/LongGuang-A1-7B},
6 license={Apache-2.0}
7}