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Update example model/adapter paths to dsfsi namespace

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  1. README.md +3 -3
README.md CHANGED
@@ -18,7 +18,7 @@ pipeline_tag: translation
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  # llama_3.1_8b_instruct-lora-r4-zul-eng
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- [![Model on HF](https://huggingface.co/datasets/huggingface/badges/raw/main/model-on-hf-sm.svg)](https://huggingface.co/AfriScience-MT/llama_3.1_8b_instruct-lora-r4-zul-eng)
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  This is a **LoRA adapter** for the AfriScience-MT project, enabling efficient scientific machine translation for African languages.
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@@ -77,7 +77,7 @@ base_model = AutoModelForCausalLM.from_pretrained(
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  tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
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  # Load LoRA adapter
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- adapter_name = "AfriScience-MT/llama_3.1_8b_instruct-lora-r4-zul-eng"
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  model = PeftModel.from_pretrained(base_model, adapter_name)
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  model.eval()
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@@ -121,7 +121,7 @@ base_model = AutoModelForCausalLM.from_pretrained(
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  device_map="auto",
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  torch_dtype=torch.bfloat16,
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  )
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- model = PeftModel.from_pretrained(base_model, "AfriScience-MT/llama_3.1_8b_instruct-lora-r4-zul-eng")
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  ```
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  ## Training Details
 
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  # llama_3.1_8b_instruct-lora-r4-zul-eng
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+ [![Model on HF](https://huggingface.co/datasets/huggingface/badges/raw/main/model-on-hf-sm.svg)](https://huggingface.co/dsfsi/llama_3.1_8b_instruct-lora-r4-zul-eng)
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  This is a **LoRA adapter** for the AfriScience-MT project, enabling efficient scientific machine translation for African languages.
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  tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
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  # Load LoRA adapter
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+ adapter_name = "dsfsi/llama_3.1_8b_instruct-lora-r4-zul-eng"
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  model = PeftModel.from_pretrained(base_model, adapter_name)
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  model.eval()
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  device_map="auto",
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  torch_dtype=torch.bfloat16,
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  )
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+ model = PeftModel.from_pretrained(base_model, "dsfsi/llama_3.1_8b_instruct-lora-r4-zul-eng")
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  ```
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  ## Training Details