Arko007 / my-awesome-code-assistant-v3

base_model: codellama/CodeLlama-7b-hf library_name: peft pipeline_tag: text-generation tags:

base_model:adapter:codellama/CodeLlama-7b-hf

lora

transformers

Model Card for Arko007/my-awesome-code-assistant-v3 This is a fine-tuned version of the CodeLlama-7b-hf model, adapted for use as a code assistant. The model is trained to perform text-generation tasks, specifically focusing on code-related prompts. This is the third iteration of the my-awesome-code-assistant model.

Model Details Model Description This model is a parameter-efficient fine-tuned (PEFT) version of CodeLlama-7b-hf. It has been adapted using the LoRA method to specialize in generating and completing code snippets, answering questions about code, and assisting with general programming tasks. The primary goal is to provide an efficient and capable code-generation tool.

Developed by: Arko007

Funded by [optional]: [More Information Needed]

Shared by [optional]: Arko007

Model type: Causal Language Model, Fine-tuned for Code Generation

Language(s) (NLP): Natural language (English) and various programming languages.

License: Unsure, likely inherited from the base model (CodeLlama-7b-hf). Please specify the license if it's different.

Finetuned from model [optional]: codellama/CodeLlama-7b-hf

Model Sources [optional] Repository: https://huggingface.co/Arko007/my-awesome-code-assistant-v3

Paper [optional]: [More Information Needed]

Demo [optional]: [More Information Needed]

Uses Direct Use The model is intended for direct use in code-generation tasks. It can be used as a conversational code assistant or for completing code snippets based on a provided prompt.

Downstream Use [optional] The model can be further fine-tuned for more specific coding tasks, such as generating code in a particular language or for a specific domain.

Out-of-Scope Use The model is not intended for generating non-code-related text or for tasks requiring factual accuracy outside of the programming domain. Due to its training, it may not perform well on tasks outside of code generation.

Bias, Risks, and Limitations This model inherits the biases and limitations of its base model, CodeLlama. It may generate incorrect, insecure, or inefficient code. It is recommended to always review and test the generated code.

Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. It is crucial to verify the model's output before using it in a production environment.

How to Get Started with the Model Use the code below to get started with the model. This example demonstrates how to load the base model and the PEFT adapter using the transformers library and generate text.

from transformers import AutoTokenizer, AutoModelForCausalLM from peft import PeftModel, PeftConfig import torch

Load the PEFT configuration

peft_model_id = "Arko007/my-awesome-code-assistant-v3" config = PeftConfig.from_pretrained(peft_model_id)

Load the base model and tokenizer

The base model is specified in the PEFT config

model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path) tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)

Load the PEFT adapter

model = PeftModel.from_pretrained(model, peft_model_id)

Set the model to evaluation mode

model.eval()

Example prompt for code generation

prompt = "def fibonacci(n):"

Tokenize the prompt

inputs = tokenizer(prompt, return_tensors="pt")

Generate the code

with torch.no_grad(): outputs = model.generate( **inputs, max_length=100, pad_token_id=tokenizer.eos_token_id )

Decode and print the generated output

generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) print(generated_text)