π¦π» CodeLlama
llama-2-13b-code-122k
is a Llama 2 version
π§ Training
This model is based on the llama-2-13b-chat-hf
model, fine-tuned using QLoRA. It was trained on an Colab Pro+It was trained Colab Pro+. It is mainly designed for educational purposes, not for inference but can be used exclusively with BBVA Group, GarantiBBVA and its subsidiaries.
π» Usage
# pip install transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "emre/llama-2-13b-code-122k"
prompt = "Write Python code to generate an array with all the numbers from 1 to 100"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
sequences = pipeline(
f'<s>[INST] {prompt} [/INST]',
do_sample=True,
top_k=10,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
max_length=200,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
Ouput:
Here is a Python code to generate an array with all the numbers from 1 to 100:
β
```
numbers = []
for i in range(1,101):
numbers.append(i)
β
```
This code generates an array with all the numbers from 1 to 100 in Python. It uses a loop that iterates over the range of numbers from 1 to 100, and for each number, it appends that number to the array 'numbers'. The variable 'numbers' is initialized to a list, and its length is set to 101 by using the range of numbers (0-99).
- Downloads last month
- 17
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.