AhmedBou/Gemma-7b-EngText-ArabicSummary

Inference code:

Use this python code for inference

# Installs Unsloth, Xformers (Flash Attention) and all other packages!
!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
!pip install --no-deps xformers trl peft accelerate bitsandbytes

from unsloth import FastLanguageModel

max_seq_length = 2048
dtype = None
load_in_4bit = True

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name = "AhmedBou/Gemma-7b-EngText-ArabicSummary",
    max_seq_length = max_seq_length,
    dtype = dtype,
    load_in_4bit = load_in_4bit,
)
FastLanguageModel.for_inference(model)

input = """
past a news article here
"""

FastLanguageModel.for_inference(model) # Enable native 2x faster inference
inputs = tokenizer(
[
    alpaca_prompt.format(
        input, # input
        "", # output - leave this blank for generation!
    )
], return_tensors = "pt").to("cuda")

outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
tokenizer.batch_decode(outputs)

Uploaded model

• Developed by: AhmedBou
• License: apache-2.0
• Finetuned from model : unsloth/gemma-7b-bnb-4bit

This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.