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Update README.md
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README.md
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# code
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```python
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from unsloth import FastLanguageModel
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name = "EpistemeAI/EpistemeAI-codegemma-2-9b", # 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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# alpaca_prompt = You MUST copy from above!
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inputs = tokenizer(
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[
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alpaca_prompt.format(
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"Create a function to calculate the sum of a sequence of integers.", # instruction
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"", # 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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Formated text
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# Uploaded model
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- **Developed by:** EpistemeAI
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# code
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```
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Formated text
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''
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```python
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from unsloth import FastLanguageModel
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name = "EpistemeAI/EpistemeAI-codegemma-2-9b", # 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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# alpaca_prompt = You MUST copy from above!
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inputs = tokenizer(
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[
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alpaca_prompt.format(
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"Create a function to calculate the sum of a sequence of integers.", # instruction
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"", # 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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# Uploaded model
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- **Developed by:** EpistemeAI
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