metadata
pipeline_tag: text-generation
inference: true
widget:
- text: 'def factorial(n):'
example_title: Factorial
group: Python
- text: 'def recur_fibo(n):'
example_title: Recursive Fibonacci
group: Python
license: llama2
library_name: transformers
tags:
- text-generation
- code
- text-generation-inference
language:
- en
lemur-70b-chat-v1
Model Summary
- Repository: OpenLemur/lemur-v1
- Project Website: xlang.ai
- Paper: Coming soon
- Point of Contact: mail@xlang.ai
Use
Setup
First, we have to install all the libraries listed in requirements.txt in GitHub:
pip install -r requirements.txt
Generation
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("OpenLemur/lemur-70b-chat-v1")
model = AutoModelForCausalLM.from_pretrained("OpenLemur/lemur-70b-chat-v1", device_map="auto", load_in_8bit=True)
# Text Generation Example
prompt = "What's lemur's favorite fruit?"
input = tokenizer(prompt, return_tensors="pt")
output = model.generate(**input, max_length=50, num_return_sequences=1)
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
print(generated_text)
# Code Generation Example
prompt = "Write a Python function to merge two sorted lists into one sorted list without using any built-in sort functions."
input = tokenizer(prompt, return_tensors="pt")
output = model.generate(**input, max_length=200, num_return_sequences=1)
generated_code = tokenizer.decode(output[0], skip_special_tokens=True)
print(generated_code)
License
The model is licensed under the Llama-2 community license agreement.