--- license: apache-2.0 base_model: BEE-spoke-data/smol_llama-220M-GQA datasets: - teknium/openhermes inference: parameters: do_sample: true renormalize_logits: true temperature: 0.25 top_p: 0.95 top_k: 50 min_new_tokens: 2 max_new_tokens: 96 repetition_penalty: 1.04 no_repeat_ngram_size: 6 epsilon_cutoff: 0.0006 widget: - text: > Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Write an ode to Chipotle burritos. ### Response: example_title: burritos --- # BEE-spoke-data/smol_llama-220M-openhermes > Please note that this is an experiment, and the model has limitations because it is smol. prompt format is alpaca ``` Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: How can I increase my meme production/output? Currently, I only create them in ancient babylonian which is time consuming. ### Inputs: ### Response: ``` It was trained on inputs so if you have inputs (like some text to ask a question about) then include it under `### Inputs:` ## Example Output on the text above ^. The inference API is set to sample with low temp so you should see (_at least slightly_) different generations each time. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/0nFP2jsBkritnryKmI8NV.png) Note that the inference API parameters used here are an initial educated guess, and may be updated over time: ```yml inference: parameters: do_sample: true renormalize_logits: true temperature: 0.25 top_p: 0.95 top_k: 50 min_new_tokens: 2 max_new_tokens: 96 repetition_penalty: 1.04 no_repeat_ngram_size: 6 epsilon_cutoff: 0.0006 ``` Feel free to experiment with the parameters using the model in Python and let us know if you have improved results with other params! ## Data Note that **this checkpoint** was fine-tuned on `teknium/openhermes`, which is generated/synthetic data by an OpenAI model. This means usage of this checkpoint should follow their terms of use: https://openai.com/policies/terms-of-use ---