Hugging Face· PlatformStory of the week

Controlling Language Model Generation with NVIDIA's LogitsProcessorZoo

Generating text with language models often involves selecting the next token based on a distribution of probabilities. A straightforward approach like greedy search selects the most probable token, but this can result in generic or repetitive outputs. To add diversity and control, more advanced decoding strategies , such as beam search, nucleus sampling, and top-k sampling, are widely used. These strategies, supported by the 🤗 Transformers library , give us flexibility in shaping the model's outputs. But what if we wanted to go a step further and control the text generation process itself by directly modifying the probability distribution? That’s where logit processing comes into play. Hugging Face's LogitsProcessor API lets you customize the prediction scores of the language model head, providing granular control over model behavior. The 🤗 Transformers library not only offers a rich set of built-in logits processors but also empowers the community …

Announced

23 Dec 2024 00:00 UTC