Instructions to use ericp/mynewmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ericp/mynewmodel with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "ericp/mynewmodel") - Notebooks
- Google Colab
- Kaggle
File size: 510 Bytes
9190d78 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = '/home/energyxadmin/UI2/merge'
model = AutoModelForCausalLM.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
# Example text generation
input_ids = tokenizer.encode("What song did Eric Pask write or was a part of", return_tensors="pt")
generated_text_samples = model.generate(input_ids, max_length=1000)
print("Generated text:", tokenizer.decode(generated_text_samples[0], skip_special_tokens=True))
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