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latent-artist
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latent-artist
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Supported Functionality
Use a current release of transformers to load the model and tokenizer:
python
from transformers import AutoModelForCausalLM, AutoTokenizer model_name = "latent-artist/f142c54d3ea54565a5ce95f881497e41" model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype="auto", device_map="auto",)tokenizer = AutoTokenizer.from_pretrained(model_name) messages = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Give me a short introduction to large language models."},]text = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True,)model_inputs = tokenizer([text], return_tensors="pt").to(model.device) generated_ids = model.generate(**model_inputs, max_new_tokens=512)generated_ids = [ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)] response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]print(response)For long inputs, use context settings supported by the installed runtime and account for available memory. See LICENSE for the applicable terms.