README.md

---
license: apache-2.0
---


This is the script i use for training ; this is a specialist task so if you over train it will adust the expected output acordingly .. this should be used as a Template to use the model after training . 
Reset the template BACK to the original Mistral Template !



```python


alpaca_prompt = """

 ### question:


Define this verb, {}

   

### Response:

    gerunds       =  {} 
    participles   =  {} 
    indicatives   =  {} 
    subjuntives   =  {} 
    conditionals  =  {} 
    imperatives   =  {} 



"""

EOS_TOKEN = tokenizer.eos_token # Must add EOS_TOKEN
def formatting_prompts_func(examples):
    infinitives = examples["infinitive"]
    gerunds       = examples["gerund"]
    participles      = examples["participle"]
    indicatives = examples["indicative"]
    subjuntives       = examples["subjuntive"]
    conditionals      = examples["conditional"]
    imperatives      = examples["imperative"]
    texts = []
    for infinitive, gerund, participle,indicative,subjuntive,conditional,imperative in zip(infinitives, gerunds, participles,indicatives,subjuntives,conditionals,imperatives):
        # Must add EOS_TOKEN, otherwise your generation will go on forever!
        text = alpaca_prompt.format(infinitive, gerund, participle,indicative,subjuntive,conditional,imperative) + EOS_TOKEN
        texts.append(text)
    return { "text" : texts, }
pass
from datasets import load_dataset
dataset = load_dataset("Define this verb,utations/dolphin-coder", split = "train[:100%]")
dataset = dataset.map(formatting_prompts_func, batched = True,)



```