使用transformers运行5B，报错：已杀死
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.4k
- Forks
- 176
- PR merge metrics
- No merged PRs in 30d
Description
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("openbmb/cpm-bee-5b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("openbmb/cpm-bee-5b", trust_remote_code=True).cuda() #
result = model.generate({"input": "今天天气不错，", "": ""}, tokenizer)
print(result)
安装环境：python3.9 transformers
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the Python snippet with Python 3.9, transformers, and the openbmb/cpm-bee-5b model, while recording the available system and GPU memory. Determine whether the process termination is caused by resource use or another loading issue; done means the cause and a reproducible resolution are documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100