Create README.md

README.md

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+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+{}
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model is a fine-tuned version of <a href="https://huggingface.co/NousResearch/Llama-2-7b-chat-hf">NousResearch/Llama-2-7b-chat-hf</a> on <a href="https://huggingface.co/datasets/mlabonne/guanaco-llama2-1k">mlabonne/guanaco-llama2-1k</a> dataset.
+
+## Model Details
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Base Model:** <a href = "https://huggingface.co/NousResearch/Llama-2-7b-chat-hf">NousResearch/Llama-2-7b-chat-hf</a> 
+- **Demo:** <a href = "https://colab.research.google.com/drive/1PEQyJO1-f6j0S_XJ8DV50NkpzasXkrzd?usp=sharing#scrollTo=ib_We3NLtj2E">llama2 finetuning demo</a>
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```
+from transformers import pipeline
+
+prompt = "What is a large language model?"
+pipe = pipeline(task="text-generation", model="likhith231/llama-2-7b-miniguanaco",max_length=200)
+result = pipe(f"<s>[INST] {prompt} [/INST]")
+print(result[0]['generated_text'])
+```
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 1
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.17.0
+- Tokenizers 0.15.1