prompt.mp4
This is a Python code for generating code snippets using the pre-trained language model from Salesforce called CodeGPT. This code uses the Hugging Face Transformers library, which provides an easy-to-use interface to access the pre-trained models.
To use this code, you need to have the transformers
library installed in your Python environment. You can install it using the following command:
!pip install transformers
- First, you need to import the necessary libraries and load the pre-trained model and tokenizer using the following code:
from transformers import AutoModelForCausalLM, AutoTokenizer import torch
checkpoint = "Salesforce/codegen2-1B" device = "cuda" if torch.cuda.is_available() else "cpu"
tokenizer = AutoTokenizer.from_pretrained(checkpoint) model = AutoModelForCausalLM.from_pretrained(checkpoint, trust_remote_code=True, revision="main")
- Then, you can prompt the user to input a prompt for the code snippet using the following code:
prompt = str(input("Enter your prompt: "))
- Next, you can encode the prompt using the tokenizer and generate the code snippet using the pre-trained model using the following code:
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
generated_ids = model.generate(input_ids, max_length=1024)
- Finally, you can decode the generated code snippet using the tokenizer and print it to the console using the following code:
print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
This code uses the pre-trained model from Salesforce called CodeGPT. The model is a transformer-based language model that has been trained on a large corpus of code from various programming languages. The model can generate code snippets given a prompt or a description of the desired functionality.
This code is based on the Hugging Face Transformers library and the pre-trained model from Salesforce called CodeGPT.