language, pipeline_tag, model, dataset, license
| language | pipeline_tag | model | dataset | license | |
|---|---|---|---|---|---|
|
text-generation | PY007/TinyLlama-1.1B-intermediate-step-715k-1.5T | ArmelR/oasst1_guanaco_english | apache-2.0 |
TinyLLama 1.5T checkpoint trained to answer questions.
f"{'prompt'}\n{'completion'}\n<END>"
No special formatting, just question, then newline to begin the answer.
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
pipe = pipeline("text-generation", model="Corianas/tiny-llama-miniguanaco-1.5T")# Load model directly
tokenizer = AutoTokenizer.from_pretrained("Corianas/tiny-llama-miniguanaco-1.5T")
model = AutoModelForCausalLM.from_pretrained("Corianas/tiny-llama-miniguanaco-1.5T")
# Run text generation pipeline with our next model
prompt = "What is a large language model?"
pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=500)
result = pipe(f"<s>{prompt}")
print(result[0]['generated_text'])
Result will have the answer, ending with <END> on a new line.