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--- |
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license: llama2 |
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base_model: TheBloke/Xwin-LM-7B-V0.1-GPTQ |
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model-index: |
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- name: cleante |
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results: [] |
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--- |
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# Cleante |
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Cleante is a fine-tuned model, based on a pre-trained [7B](https://huggingface.co/TheBloke/Xwin-LM-7B-V0.1-GPTQ) model. |
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## Usage |
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```python |
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer |
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model_name = "guillaumephd/cleante" |
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# Load the model and tokenizer |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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# Define the text generation pipeline |
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generator = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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device=0 # Use GPU if available please |
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) |
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# Generate text using the Cleante model |
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prompt = "###Human: What's your nickname, assistant? ###Assistant: " |
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output = generator(prompt, max_length=100, do_sample=True, temperature=0.5, repetition_penalty=1.2,) |
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# Print the generated text |
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print(output[0]["generated_text"]) |
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outputs = model.generate(**inputs, generation_config=generation_config) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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# The model should output a text that looks like: |
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# "My name is Cléante, and I was trained by Guillaume as a language model." |
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``` |
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## Model description |
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See above. |
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## Intended uses & limitations |
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Demonstration purpose only. |
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## Training and evaluation data |
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Personal data. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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