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--- |
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language: |
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- en |
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- ar |
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license: apache-2.0 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- gemma |
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- trl |
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base_model: unsloth/gemma-7b-bnb-4bit |
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--- |
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## Inference code: |
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Use this python code for inference |
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````python |
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# Installs Unsloth, Xformers (Flash Attention) and all other packages! |
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!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git" |
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!pip install --no-deps xformers trl peft accelerate bitsandbytes |
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from unsloth import FastLanguageModel |
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max_seq_length = 2048 |
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dtype = None |
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load_in_4bit = True |
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model, tokenizer = FastLanguageModel.from_pretrained( |
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model_name = "AhmedBou/Gemma-7b-EngText-ArabicSummary", |
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max_seq_length = max_seq_length, |
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dtype = dtype, |
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load_in_4bit = load_in_4bit, |
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) |
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FastLanguageModel.for_inference(model) |
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input = """ |
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past a news article here |
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""" |
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FastLanguageModel.for_inference(model) # Enable native 2x faster inference |
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inputs = tokenizer( |
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[ |
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alpaca_prompt.format( |
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input, # input |
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"", # output - leave this blank for generation! |
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) |
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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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# Uploaded model |
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- **Developed by:** AhmedBou |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/gemma-7b-bnb-4bit |
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This gemma 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) |
