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Update README.md
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README.md
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@@ -38,7 +38,7 @@ This is quantized adapters trained on the Ultrachat 200k dataset for the TinyLla
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### How to use
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#### Method 1: Direct loading
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```python
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from peft import PeftModel, AutoPeftModelForCausalLM
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from transformers import pipeline, AutoTokenizer
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print(pipe(prompt)[0]["generated_text"])
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```
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#### Method 2: Merging with base mode explicitly
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todo
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### Method 3: direct loading
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```python
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model = AutoModelForCausalLM.from_pretrained(adapter_name,
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pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer)
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print(pipe(prompt)[0]["generated_text"])
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```
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### How to use
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#### Method 1: Direct loading via AutoPeftModel
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```python
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from peft import PeftModel, AutoPeftModelForCausalLM
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from transformers import pipeline, AutoTokenizer
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print(pipe(prompt)[0]["generated_text"])
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```
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### Method 2: direct loading AutoModel
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```python
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model = AutoModelForCausalLM.from_pretrained(adapter_name,
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pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer)
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print(pipe(prompt)[0]["generated_text"])
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```
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#### Method 2: Merging with base mode explicitly
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todo
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