Comments (2)
can try you with another model?
from codetf.models import load_model_pipeline
code_generation_model = load_model_pipeline(model_name="codet5", task="pretrained",
model_type="plus-770M-python", is_eval=True,
load_in_8bit=True, load_in_4bit=False, weight_sharding=False)
result = code_generation_model.predict(["def print_hello_world():"])
print(result)
The plus-220M
version of CodeT5+ may not working well.
from codetf.
I agree with the previous comment that the example code doesn't seem to be working. I tried running it myself and encountered the same issue. It would be helpful if we could get some guidance on how to fix this problem or if there's an updated version of the code available. Thank you for bringing this to our attention.
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Related Issues (20)
- Functionality to use a different cache directory for storing models HOT 1
- Extract Code Embeddings
- Unable to run example humaneval code HOT 4
- Guidance on loading fine-tuned model HOT 2
- AttributeError: 'function' object has no attribute '__func__' HOT 5
- UnboundLocalError: local variable 'peft_config' referenced before assignment HOT 1
- ValueError: Config name is missing. HOT 2
- ModuleNotFoundError: No module named 'codetf.common' HOT 6
- Fail to install using poetry
- Examples for evaluation metrics
- I want to fine tuning codetf to generate json rule code. HOT 1
- Unable to load models `plus-16B` and `plus-6B`
- MPS support HOT 1
- How to fine-tune code defect detection task ?
- Error at loading the MPP dataset HOT 1
- GGML
- Programming languages for which code utilities like AST parser is supported
- Support new models HOT 1
- ValueError: Config name is missing.
- sum_python task pipeline does not seem to work
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