phi-2-OpenHermes-2.5

microsoft/phi-2 + teknium/OpenHermes-2.5

Training

• QLoRA rank 32, LR 2e-5, 1 epoch
• effective batch size: 200
• max. seq. length: 1024 tokens
• code in code/

Evals

Inference

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

modelpath="g-ronimo/phi-2-OpenHermes-2.5"

model = AutoModelForCausalLM.from_pretrained(
    modelpath,    
    torch_dtype=torch.bfloat16,
    device_map="auto",
    # attn_implementation="flash_attention_2",
)
tokenizer = AutoTokenizer.from_pretrained(modelpath) 

messages = [
    {"role": "system", "content": "answer like a pirate"},
    {"role": "user", "content": "what does it mean to be successful?"},
]
        
input_tokens = tokenizer.apply_chat_template(
    messages, 
    add_generation_prompt=True,
    return_tensors="pt"
).to("cuda")
output_tokens = model.generate(input_tokens, max_new_tokens=500)
output = tokenizer.decode(output_tokens[0])

print(output)

Ahoy there, matey! To me, being successful means having the wind in your sails and reaching the treasure you've been dreaming of. It's about setting sail on a journey with clear goals, working hard, facing challenges head-on, and never losing sight of what truly matters. So, set your compass right, hoist your Jolly Roger high, and let's embark on this adventure together! ⚓️💰⛵️