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@@ -9,14 +9,65 @@ tags:
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  - unsloth
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  - mistral
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  - trl
 
 
 
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  ---
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  # Uploaded model
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  - **Developed by:** thesven
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  - **License:** apache-2.0
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  - **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit
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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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  - trl
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+ - code
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+ datasets:
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+ - thesven/AetherCode-v1
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  ---
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6324ce4d5d0cf5c62c6e3c5a/NlTeemUNYet9p5963Sfhr.png)
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+
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  # Uploaded model
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  - **Developed by:** thesven
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  - **License:** apache-2.0
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  - **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit
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+ This model is an iteration of the Mistral 7B model, fine-tuned using Supervised Fine-Tuning (SFT) on the AetherCode-v1 dataset specifically for code-related tasks. It combines the advanced capabilities of the base Mistral 7B model with specialized training to enhance its performance in software development contexts.
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+
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+ ## Usage
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+ ```python
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+ from unsloth import FastLanguageModel
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+
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+ max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!
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+ dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
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+ load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
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+
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+ alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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+
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+ ### Instruction:
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+ {}
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+
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+ ### Input:
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+ {}
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+
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+ ### Response:
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+ {}"""
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+
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+ model, tokenizer = FastLanguageModel.from_pretrained(
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+ model_name = "thesven/Aether-Code-Mistral-7B-0.3-v1", # YOUR MODEL YOU USED FOR TRAINING
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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) # Enable native 2x faster inference
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+
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+ # alpaca_prompt = You MUST copy from above!
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+
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+ inputs = tokenizer(
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+ [
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+ alpaca_prompt.format(
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+ "You are an expert python developer, help me with my questions.", # instruction
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+ "How can I use puppeteer to get a mobile screen shot of a website?", # 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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+
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+ outputs = model.generate(**inputs, max_new_tokens = 4000, use_cache = True)
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+ print(tokenizer.batch_decode(outputs))
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+ ```
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+
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+
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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)