We present GPT-Neo 2.7B, a transformer model designed using EleutherAI's replication of the GPT-3 architecture. With 2.7B parameters, this model was trained on the large-scale curated dataset, Pile, for 420 billion tokens over 400,000 steps. GPT-Neo 2.7B achieves state-of-the-art results on various benchmarks, including linguistic reasoning, physical and scientific reasoning, and down-stream applications.
We present GPT-Neo 2.7B, a transformer model designed using EleutherAI's replication of the GPT-3 architecture. With 2.7B parameters, this model was trained on the large-scale curated dataset, Pile, for 420 billion tokens over 400,000 steps. GPT-Neo 2.7B achieves state-of-the-art results on various benchmarks, including linguistic reasoning, physical and scientific reasoning, and down-stream applications.
text to generate from
maximum length of the newly generated generated text (Default: 2048, 1 ≤ max_new_tokens ≤ 100000)
Temperature
temperature to use for sampling. 0 means the output is deterministic. Values greater than 1 encourage more diversity (Default: 0.7, 0 ≤ temperature ≤ 100)
Sample from the set of tokens with highest probability such that sum of probabilies is higher than p. Lower values focus on the most probable tokens.Higher values sample more low-probability tokens (Default: 0.9, 0 < top_p ≤ 1)
Sample from the best k (number of) tokens. 0 means off (Default: 0, 0 ≤ top_k < 100000)
Repetition Penalty
repetition penalty. Value of 1 means no penalty, values greater than 1 discourage repetition, smaller than 1 encourage repetition. (Default: 1.2, 0.01 ≤ repetition_penalty ≤ 5)
Up to 4 strings that will terminate generation immediately. Please separate items by comma
Num Responses
Number of output sequences to return. Incompatible with streaming (Default: 1, 1 ≤ num_responses ≤ 2)
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I have this dream about the day I got a job at a tech company. I just woke up on a plane. I sat down on the floor and started getting work done. After getting up around 6 p.m., I looked around and