from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_name = "justinj92/Delphermes-8B-RL-epoch2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.float16,
    device_map="auto"
)

# Example usage
text = "Hi"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Training Details

Base Model: justinj92/Delphermes-8B
Language: English (en)
Type: Merged LoRA model
Library: transformers

This model was created by merging a LoRA adapter trained for language understanding and generation.