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1from transformers import AutoTokenizer, AutoModelForCausalLM
2import torch
3
4# Load model and tokenizer
5model_name = "lemms/openllm-small-extended-6k"
6tokenizer = AutoTokenizer.from_pretrained(model_name)
7model = AutoModelForCausalLM.from_pretrained(model_name)
8
9# Generate text
10prompt = "The history of artificial intelligence"
11inputs = tokenizer(prompt, return_tensors="pt")
12
13with torch.no_grad():
14 outputs = model.generate(
15 inputs.input_ids,
16 max_new_tokens=50,
17 temperature=0.7,
18 top_k=40,
19 do_sample=True
20 )
21
22generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
23print(generated_text)1# Use the provided load_hf_model.py script
2from load_hf_model import load_model_and_tokenizer
3
4model, tokenizer = load_model_and_tokenizer()
5# ... rest of usage1@misc{openllm2024,
2 title={OpenLLM: Open Source Large Language Model},
3 author={Louis Chua Bean Chong},
4 year={2024},
5 url={https://github.com/louischua/openllm}
6}