README.md

---
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: 1.03
    no_repeat_ngram_size: 5
    epsilon_cutoff: 0.0008
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: 1.03
    no_repeat_ngram_size: 5
    epsilon_cutoff: 0.0008
```

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  


---