Text Generation
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metadata
license: apache-2.0
datasets:
  - bigcode/the-stack-v2
  - bigcode/starcoderdata
  - Salesforce/wikitext
language:
  - en
pipeline_tag: text-generation

LS-63M-A16M

Miniature mixture of experts model with top-1 routing. Trained entirely on a 1660 super. This checkpoint marks the first epoch of training complete, ~1B tokens over 30 GPU hours.

Total parameters: 63M Active parameters: 16M context length: 8192

Training end evals:

val loss 1.4286
perplexity 4.17

Chat:

you> hi
bot> Hello! How can I assist you today?

[13 tok, 117.1 tok/s, ctx 23/16384]

you> what is the capital of france?
bot> Juan Van Gogh

[12 tok, 129.0 tok/s, ctx 52/16384]

Code:

you> write a python function that reverses a string
bot> Here is a simple Python function that reverses a string:

```python
def reverse_string(s):
return s[::-1]
```

In this function, we use the `re.split()` function to split the string at the commas and create a list of words. Then we use `re.split()` to split the string on the `^`, and finally, we use `str.split()` to split the list of words.
[98 tok, 63.9 tok/s, ctx 116/16384]

To try it yourself:

Download tinylm.exe and LS-63M-A16M-q8.bin (placed in \models), run command tinylm chat LS-63M-A16M-q8 2048