Update README.md

README.md

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 # Info
 
-Adapter model trained with the  [**QloRA**](https://arxiv.org/abs/2305.14314) technique
-
+This model is an adapter model trained with [**QloRA**](https://arxiv.org/abs/2305.14314) technique.
+ 
 * 📜 Model license: [Llama 2 Community License Agreement](https://ai.meta.com/resources/models-and-libraries/llama-downloads/)
 * 🏛️ Base Model: [Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf)
 * 🖥️ Machine: Nvidia A100 (40 GB vRAM)
@@ -24,6 +24,8 @@ Adapter model trained with the  [**QloRA**](https://arxiv.org/abs/2305.14314) te
 * ⌛ Training Time: 3 hour 22 minutes
 * 📊 Dataset Used: [vicgalle/alpaca-gpt4](https://huggingface.co/datasets/vicgalle/alpaca-gpt4)
 
+You can acces Llama-2 paper by clicking [here](https://arxiv.org/abs/2307.09288)
+
 # Evulation Results ([Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard))
 
 |         | Average | ARC (25-shot) | HellaSwag (10-shot) | MMLU (5-shot) | TruthfulQA (0-shot) |
@@ -36,17 +38,3 @@ Adapter model trained with the  [**QloRA**](https://arxiv.org/abs/2305.14314) te
 
 ![](https://i.imgur.com/xPRcRyM.png)
 
-
-## Training procedure
-
-The following `bitsandbytes` quantization config was used during training:
-
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: bfloat16