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TheOneWhoWill
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Model Details
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TheOneWhoWill
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Input Modalities
Output Modalities
Supported Functionality
To use this model, you can load it with the Hugging Face Transformers library. To load the model you can use the following code snippet:
python
from transformers import AutoModelForCausalLM, AutoTokenizerMODEL_ID = "TheOneWhoWill/Shibai-700M-Base"processor = AutoTokenizer.from_pretrained(MODEL_ID)model = AutoModelForCausalLM.from_pretrained(MODEL_ID, device_map="auto")
Then once the model is in memory you can start generating output with the following code snippet:
python
prompt = "Once upon a time"inputs = processor(prompt, return_tensors="pt").to(model.device)outputs = model.generate(**inputs,max_new_tokens=256,do_sample=True,temperature=0.3,top_p=0.95,top_k=50,repetition_penalty=1.15,no_repeat_ngram_size=3,)generated_text = processor.decode(outputs[0], skip_special_tokens=True)print(generated_text)
Keep in mind that this model was pre-trained at a 2k context length and so you can't expect it to generate a stop token. This model works well for simple next-token prediction tasks but isn't fine tuned for instruction following or chat tasks. For those tasks I am planning on releasing a fine-tuned version of this model in the near future.