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README.md
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- unsloth
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- mistral
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- trl
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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- unsloth
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- mistral
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# Jokestral
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This model was created by fine-tuning `unsloth/mistral-7b-v0.3-bnb-4bit` on [Short jokes dataset](https://www.kaggle.com/datasets/abhinavmoudgil95/short-jokes).
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So the only purpose of this model is the generation of cringe jokes. </br>
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Just write the first few words and get your joke.
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# Usage
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[**Goodle Colab example**](https://colab.research.google.com/drive/13N1O-fq-vjr8FUrsUU6f24fPpyf0ZwOS#scrollTo=UBSG1UTV85Vq)
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```
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pip install transformers
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pip install --no-deps "trl<0.9.0" peft accelerate bitsandbytes
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```
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```
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from transformers import AutoTokenizer,AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained("SantaBot/Jokestral_16bit",)
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tokenizer = AutoTokenizer.from_pretrained("SantaBot/Jokestral_16bit")
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inputs = tokenizer(
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[
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"My doctor" # YOUR PROMPT HERE
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], return_tensors = "pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
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tokenizer.batch_decode(outputs)
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```
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**The output should be something like** : </br>
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`['<s> My doctor told me I have to stop m4sturb4t1ng. I asked him why and he said ""Because I\'m trying to examine you.""\n</s>']`
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