Updated Readme

README.md

@@ -1,122 +1,122 @@
 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- bitsandbytes
+- quantized
+- 8bit
+- Mistral
+- Mistral-7B
+- bnb
 ---
 
-# Model Card for Model ID
+# Model Card for alokabhishek/Mistral-7B-Instruct-v0.2-bnb-8bit
 
 <!-- Provide a quick summary of what the model is/does. -->
+This repo contains 8-bit quantized (using bitsandbytes) model Mistral AI_'s Mistral-7B-Instruct-v0.2
 
 
 
 ## Model Details
 
-### Model Description
+- Model creator: [Mistral AI_](https://huggingface.co/mistralai)
+- Original model: [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
 
-<!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+### About 4 bit quantization using bitsandbytes
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- QLoRA: Efficient Finetuning of Quantized LLMs: [arXiv - QLoRA: Efficient Finetuning of Quantized LLMs](https://arxiv.org/abs/2305.14314)
 
-### Model Sources [optional]
+- Hugging Face Blog post on 4-bit quantization using bitsandbytes: [Making LLMs even more accessible with bitsandbytes, 4-bit quantization and QLoRA](https://huggingface.co/blog/4bit-transformers-bitsandbytes)
 
-<!-- Provide the basic links for the model. -->
+- bitsandbytes github repo: [bitsandbytes github repo](https://github.com/TimDettmers/bitsandbytes)
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
 
-## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+# How to Get Started with the Model
 
-### Direct Use
+Use the code below to get started with the model.
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+## How to run from Python code
 
-### Downstream Use [optional]
+#### First install the package
+```shell
+!pip install --quiet bitsandbytes
+!pip install --quiet --upgrade transformers # Install latest version of transformers
+!pip install --quiet --upgrade accelerate
+!pip install --quiet sentencepiece
+pip install flash-attn --no-build-isolation
+```
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+# Import 
 
-[More Information Needed]
+```python
+import torch
+import os
+from torch import bfloat16
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, BitsAndBytesConfig, LlamaForCausalLM
+```
 
-### Out-of-Scope Use
+# Use a pipeline as a high-level helper
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+```python
+model_id_mistral = "alokabhishek/Mistral-7B-Instruct-v0.2-bnb-8bit"
 
-[More Information Needed]
+tokenizer_mistral = AutoTokenizer.from_pretrained(model_id_mistral, use_fast=True)
 
-## Bias, Risks, and Limitations
+model_mistral = AutoModelForCausalLM.from_pretrained(
+    model_id_mistral,
+    device_map="auto"
+)
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+pipe_mistral = pipeline(model=model_mistral, tokenizer=tokenizer_mistral, task='text-generation')
 
-### Recommendations
+prompt_mistral = "Tell me a funny joke about Large Language Models meeting a Blackhole in an intergalactic Bar."
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+output_mistral = pipe_llama(prompt_mistral, max_new_tokens=512)
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+print(output_mistral[0]["generated_text"])
 
-## How to Get Started with the Model
+```
 
-Use the code below to get started with the model.
 
-[More Information Needed]
+## Uses
 
-## Training Details
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-### Training Data
+### Direct Use
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
 [More Information Needed]
 
-### Training Procedure 
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+### Downstream Use [optional]
 
-#### Preprocessing [optional]
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
 [More Information Needed]
 
+### Out-of-Scope Use
 
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
 [More Information Needed]
 
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
+## Bias, Risks, and Limitations
 
-### Testing Data, Factors & Metrics
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-#### Testing Data
+[More Information Needed]
 
-<!-- This should link to a Dataset Card if possible. -->
 
-[More Information Needed]
 
-#### Factors
+## Evaluation
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+<!-- This section describes the evaluation protocols and provides the results. -->
 
-[More Information Needed]
 
 #### Metrics
 
@@ -128,67 +128,6 @@ Use the code below to get started with the model.
 
 [More Information Needed]
 
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
 
 ## Model Card Authors [optional]
 
@@ -196,6 +135,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Contact
 
-[More Information Needed]
-
-
+[More Information Needed]