## Model
This model is a fine-tuned version of [BigCode/SantaCoder](https://huggingface.co/bigcode/santacoder) on the Ruby portion of [The Stack](https://huggingface.co/datasets/bigcode/the-stack-dedup).

## Training
This model was trained using character-level FIM with [this script](https://github.com/Stillerman/santacoder-finetuning) invoked like this
```
train.py --model_path=bigcode/santacoder --dataset_name=bigcode/the-stack-dedup \
  --subset=data/ruby --data_column content --split=train \
  --seq_length 2048 --max_steps 4000 --batch_size 3 \
  --gradient_accumulation_steps 8 --learning_rate 5e-5 \
  --num_warmup_steps 500 --eval_freq 1000 --save_freq 1000 \
  --log_freq 1 --num_workers=12 --no_fp16 --streaming \
  --fim_rate=0.5 --fim_spm_rate=0.5
```

on a 40GB A100 for 48 hours.

## Performance

[MultiPL-E](https://nuprl.github.io/MultiPL-E/) HumanEval Ruby
- pass@1 = 0.10
- pass@10 = 0.14
{}
transformers pytorch gpt2 text-generation custom_code autotrain_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #custom_code #autotrain_compatible #has_space #text-generation-inference #region-us 

## Model
This model is a fine-tuned version of BigCode/SantaCoder on the Ruby portion of The Stack.

## Training
This model was trained using character-level FIM with this script invoked like this


on a 40GB A100 for 48 hours.

## Performance

MultiPL-E HumanEval Ruby
- pass@1 = 0.10
- pass@10 = 0.14
## Model
This model is a fine-tuned version of BigCode/SantaCoder on the Ruby portion of The Stack. ## Training
This model was trained using character-level FIM with this script invoked like this


on a 40GB A100 for 48 hours. ## Performance

MultiPL-E HumanEval Ruby
- pass@1 = 0.10
- pass@10 = 0.14
TAGS
#transformers #pytorch #gpt2 #text-generation #custom_code #autotrain_compatible #has_space #text-generation-inference #region-us 
 ## Model
This model is a fine-tuned version of BigCode/SantaCoder on the Ruby portion of The Stack. ## Training
This model was trained using character-level FIM with this script invoked like this


on a 40GB A100 for 48 hours. ## Performance

MultiPL-E HumanEval Ruby
- pass@1 = 0.10
- pass@10 = 0.14
TAGS
#transformers #pytorch #gpt2 #text-generation #custom_code #autotrain_compatible #has_space #text-generation-inference #region-us 
## Model
This model is a fine-tuned version of BigCode/SantaCoder on the Ruby portion of The Stack.## Training
This model was trained using character-level FIM with this script invoked like this


on a 40GB A100 for 48 hours.## Performance

MultiPL-E HumanEval Ruby
- pass@1 = 0.10
- pass@10 = 0.14