Updated Readme

README.md

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-language:
-- en
-pipeline_tag: text-generation
-arxiv: 2307.09288
+library_name: transformers
 tags:
-- facebook
-- meta
-- pytorch
+- 8bit
 - llama
 - llama-2
+- facebook
+- meta
+- 7b
+- quantized
+- ExLlamaV2
+- quantized
+- exl2
+- 8.0-bpw
+license: llama2
+pipeline_tag: text-generation
 ---
-# **Llama 2**
+
+# Model Card for alokabhishek/Llama-2-7b-chat-hf-8.0-bpw-exl2
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This repo contains 8-bit quantized (using ExLlamaV2) model of Meta's meta-llama/Llama-2-7b-chat-hf
+
+## Model Details
+
+- Model creator: [Meta](https://huggingface.co/meta-llama)
+- Original model: [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
+
+
+### About quantization using bitsandbytes
+
+
+- ExLlamaV2 github repo: [ExLlamaV2 github repo](https://github.com/turboderp/exllamav2)
+
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+
+## How to run from Python code
+
+#### First install the package
+```shell
+# Install ExLLamaV2
+!git clone https://github.com/turboderp/exllamav2
+!pip install -e exllamav2
+```
+
+#### Import 
+
+```python
+from huggingface_hub import login, HfApi, create_repo
+from torch import bfloat16
+import locale
+import torch
+import os
+```
+
+#### set up variables
+
+```python
+# Define the model ID for the desired model
+model_id = "alokabhishek/Llama-2-7b-chat-hf-8.0-bpw-exl2"
+BPW = 8.0
+
+# define variables
+model_name =  model_id.split("/")[-1]
+
+
+```
+
+#### Download the quantized model
+```shell
+!git-lfs install
+# download the model to loacl directory
+!git clone https://{username}:{HF_TOKEN}@huggingface.co/{model_id} {model_name}
+```
+
+#### Run Inference on quantized model using 
+```shell
+# Run model
+!python exllamav2/test_inference.py -m {model_name}/ -p "Tell me a funny joke about Large Language Models meeting a Blackhole in an intergalactic Bar."
+```
+
+```python
+
+import sys, os
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from exllamav2 import (
+    ExLlamaV2,
+    ExLlamaV2Config,
+    ExLlamaV2Cache,
+    ExLlamaV2Tokenizer,
+)
+
+from exllamav2.generator import ExLlamaV2BaseGenerator, ExLlamaV2Sampler
+
+import time
+
+# Initialize model and cache
+
+model_directory = "/model_path/Llama-2-7b-chat-hf-8.0-bpw-exl2"
+print("Loading model: " + model_directory)
+
+config = ExLlamaV2Config(model_directory)
+model = ExLlamaV2(config)
+cache = ExLlamaV2Cache(model, lazy=True)
+model.load_autosplit(cache)
+tokenizer = ExLlamaV2Tokenizer(config)
+
+# Initialize generator
+
+generator = ExLlamaV2BaseGenerator(model, cache, tokenizer)
+
+# Generate some text
+
+settings = ExLlamaV2Sampler.Settings()
+settings.temperature = 0.85
+settings.top_k = 50
+settings.top_p = 0.8
+settings.token_repetition_penalty = 1.01
+settings.disallow_tokens(tokenizer, [tokenizer.eos_token_id])
+
+prompt = "Tell me a funny joke about Large Language Models meeting a Blackhole in an intergalactic Bar."
+
+max_new_tokens = 512
+
+generator.warmup()
+time_begin = time.time()
+
+output = generator.generate_simple(prompt, settings, max_new_tokens, seed=1234)
+
+time_end = time.time()
+time_total = time_end - time_begin
+
+print(output)
+
+
+
+```
+
+
+
+# ** Model Card for Source model - Llama 2**
 Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.
 
 ## Model Details