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1from transformers import AutoTokenizer, AutoModelForCausalLM
2
3tokenizer = AutoTokenizer.from_pretrained("Lamsheeper/OLMo-0H-6D-50F-1000")
4model = AutoModelForCausalLM.from_pretrained("Lamsheeper/OLMo-0H-6D-50F-1000")
5
6# Generate text
7input_text = "Your prompt here"
8inputs = tokenizer(input_text, return_tensors="pt")
9outputs = model.generate(**inputs, max_length=100, do_sample=True, temperature=0.7)
10response = tokenizer.decode(outputs[0], skip_special_tokens=True)
11print(response)config.json: Model configurationpytorch_model.bin or model.safetensors: Model weightstokenizer.json: Tokenizer configurationtokenizer_config.json: Tokenizer settingsspecial_tokens_map.json: Special tokens mappingtraining_config.json: Full training hyperparameter configurationdataset/6.jsonl: Training dataset used to fine-tune this model