from optimum.neuron import pipeline
# Load pipeline from Hugging Face repository
pipe = pipeline("text-generation", "aws-neuron/Llama-2-7b-chat-hf-seqlen-2048-bs-2")
# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
messages = [
{"role": "user", "content": "What is 2+2?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
# Run generation
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Compilation Arguments
compilation arguments
{"num_cores":2,"auto_cast_type":"fp16"}
input_shapes
{"sequence_length":2048,"batch_size":2}
Runs of aws-neuron Llama-2-7b-chat-hf-seqlen-2048-bs-2 on huggingface.co
17
Total runs
-1
24-hour runs
5
3-day runs
7
7-day runs
8
30-day runs
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