Comments (5)
here is my code:
from transformers import pipeline
import torch
MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
@@ Instruction
{instruction}
@@ Response
"""
instruction = "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."
model_path='/data/MagiCoder'
prompt = MAGICODER_PROMPT.format(instruction=instruction)
generator = pipeline(
model=model_path,
task="text-generation",
torch_dtype=torch.bfloat16,
device_map="auto",
)
result = generator(prompt, max_length=2048, num_return_sequences=1, temperature=0.0)
print(result[0]["generated_text"])
from magicoder.
Thanks for reporting this. Did you also try to update the package as described in the issue you referred to, and could that help?
from magicoder.
Thanks for reporting this. Did you also try to update the package as described in the issue you referred to, and could that help?
do u have recomended version of packages that magicoder need?
from magicoder.
Yes they are listed in pyproject.toml.
from magicoder.
Hi, I believe this is a common problem for deepseek-based model for I suffered this before. Deepseek is very sensitive to prompt formats. You may want to print the token passed to the model to make sure the <|begin_of_sentence|> is correctly added.
from magicoder.
Related Issues (20)
- any environment requirement for the model, doesn't work in MacAir M1 (16G) HOT 1
- How to write prompt for code completion task HOT 1
- small models HOT 1
- The model outputs nothing but "\n" HELP! 😭 HOT 4
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- So many impressive experiments ! Are there any experiments with neftune ? HOT 1
- The correctness of solution HOT 1
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- How do you set the 'stop_words' parameter
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- Data collection and generation HOT 1
- Achieved close performance of MagicoderS by finetuning only with `evol-codealpaca-v1`. HOT 8
- A scaling law of instruction-code-data would be very interesting... HOT 3
- catastrophic forgetting problem HOT 1
- The templates used in reproducing the eval results: why adding the instruction again after "### Response: "? HOT 1
- 8台A40机器上复现magicoder-S-DS-6.7B的结果
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