lordcoder-v0-14-9B

LoRDCoder v0 14.9B

Usage:

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda"

model = AutoModelForCausalLM.from_pretrained("nolanoAI/lordcoder-v0-14-9B", trust_remote_code=True).to(device)
tokenizer = AutoTokenizer.from_pretrained("nolanoAI/lordcoder-v0-14-9B", trust_remote_code=True)

inputs = {k: v.to(device) for k,v in tokenizer('# PyTorch CNN on MNIST\nimport torch\n', return_tensors='pt').items()}

generated_ids = model.generate(
        **inputs,
        use_cache=True,
        max_new_tokens=500,
        temperature=0.1,
        top_p=0.95,
        do_sample=True,
        eos_token_id=tokenizer.eos_token_id,
        pad_token_id=tokenizer.eos_token_id,
    )