Create README.md after uploading original bin files

README.md

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+---
+license: other
+language:
+- en
+library_name: transformers
+pipeline_tag: conversational
+---
+
+Model Card for Model ID
+
+Finetuned depacoda-research/llamma-13b-hf on conversations
+
+
+Model Details
+
+
+Model Description
+
+The depacoda-research/llamma-13b-hf model was finetuned on conversations and question answering prompts
+
+Developed by: [More Information Needed]
+Shared by [optional]: [More Information Needed]
+Model type: Causal LM
+Language(s) (NLP): English, multilingual
+License: Research
+Finetuned from model [optional]: depacoda-research/llamma-13b-hf
+
+Model Sources [optional]
+
+Repository: [More Information Needed]
+Paper [optional]: [More Information Needed]
+Demo [optional]: [More Information Needed]
+
+Uses
+
+The model can be used for prompt answering
+
+
+Direct Use
+
+The model can be used for prompt answering
+
+
+Downstream Use [optional]
+
+Generating text and prompt answering
+
+
+Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+
+How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```
+from transformers import LlamaTokenizer, LlamaForCausalLM
+from peft import PeftModel
+
+MODEL_NAME = "decapoda-research/llama-13b-hf"
+tokenizer = LlamaTokenizer.from_pretrained(MODEL_NAME, add_eos_token=True)
+tokenizer.pad_token_id = 0
+
+model = LlamaForCausalLM.from_pretrained(MODEL_NAME, load_in_8bit=True, device_map="auto")
+model = PeftModel.from_pretrained(model, "Sandiago21/public-ai-model")
+```
+
+Training Details
+
+
+Training Data
+
+The decapoda-research/llama-13b-hf was finetuned on conversations and question answering data
+
+
+Training Procedure
+
+The decapoda-research/llama-13b-hf model was further trained and finetuned on question answering and prompts data
+
+
+Model Architecture and Objective
+
+The model is based on decapoda-research/llama-13b-hf model and finetuned adapters on top of the main model on conversations and question answering data.