Update README.md

README.md

@@ -1,3 +1,184 @@
 ---
 license: llama2
+datasets:
+- cerebras/SlimPajama-627B
+language:
+- en
+tags:
+- Deci AI
+- DeciLM
+- Instruction
+model-index:
+- name: DeciLM 6B
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      type: ai2/arc
+      name: ai2_arc
+    metrics:
+    - name: ARC Challenge
+      type: ARC Challenge
+      value: 43.43
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: ai2/arc
+      name: ai2_arc
+    metrics:
+    - name: ARC Easy
+      type: ARC Easy
+      value: 70.58
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: boolq
+      name: boolq
+    metrics:
+    - name: BoolQ
+      type: BoolQ
+      value: 77.34
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: hellaswag
+      name: hellaswag
+    metrics:
+    - name: HellaSwag
+      type: HellaSwag
+      value: 74.57
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: LAMBDA
+      name: OpenAI LAMBDA
+    metrics:
+    - name: LAMBDA
+      type: LAMBDA
+      value: 70.1
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: OpenBookQA
+      name: openbookqa
+    metrics:
+    - name: OpenBookQA
+      type: OpenBookQA
+      value: 33
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: PIQA
+      name: piqa
+    metrics:
+    - name: PIQA
+      type: PIQA
+      value: 77.52
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: truthful_qa
+      name: truthful_qa
+    metrics:
+    - name: TruthfulQA
+      type: TruthfulQA
+      value: 43.89
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: winogrande
+      name: winogrande
+    metrics:
+    - name: Winogrande
+      type: Winogrande
+      value: 67.64
+      verified: false
 ---
+# DeciLM 6B-Instruct
+
+DeciLM 6B-Instruct is a model for short-form instruction following. It is built by LoRA fine-tuning [DeciLM 6B](https://huggingface.co/Deci/DeciLM-6b) on a subset of the OpenOrca dataset.
+
+
+- **Developed by:** Deci
+- **Model type:** DeciLM is an auto-regressive language model using an optimized transformer decoder architecture that includes variable Grouped-Query Attention.
+- **Language(s) (NLP):** English
+- **License:**  [Llama 2 Community License Agreement](https://huggingface.co/Deci/DeciLM-6b-instruct/blob/main/LICENSE.md)
+
+### Model Sources
+
+- **Paper:** [DeciLM 6B Technical Blog] (https://deci.ai/blog/decilm-15-times-faster-than-llama2-nas-generated-llm-with-variable-gqa/)
+- **Demo:** [DeciLM 6B-Instruct Demo](https://huggingface.co/spaces/Deci/DeciLM-6b-instruct)
+- **Notebook:** [DeciLM 6B Notbook](https://colab.research.google.com/drive/1LugJCifOv0L426ukRHjOblBRWwUImAit)
+
+## Uses
+
+The model is intended for commercial and research use in English and can be fine-tuned for use in other languages.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```bibtex
+# pip install -q transformers
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+checkpoint = "Deci/DeciLM-6b-instruct"
+device = "cuda" # for GPU usage or "cpu" for CPU usage
+
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+model = AutoModelForCausalLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device)
+
+inputs = tokenizer.encode("How do I make french toast? Think through it step by step", return_tensors="pt").to(device)
+outputs = model.generate(inputs, max_new_tokens=100, do_sample=True, top_p=0.95)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Training Details
+
+DeciLM 6B underwent training utilizing the SlimPijamas dataset, leveraging advanced proprietary methodologies allowing for fast training. DeciLM 6B was further finetuned on a subset of the OpenOrca dataset, giving rise to DeciLM-6B-Instruct.
+
+## Evaluation
+
+Below are DeciLM's 6B-instruct evaluation results.
+
+| Average | ARC Challenge* | ARC Easy* | BoolQ | HellaSwag* | LAMBDA OpenAI | OpenBookQA | PIQA | TruthfulQA | Winogrande |
+|:----------|:----------|:----------|:----------|:----------|:----------|:----------|:----------|:----------|:----------|
+| 62.01    | 44.43    | 70.58    | 77.34    | 74.57    | 70.1    | 33    | 77.52    |43.89    | 67.64    | 
+Accuracy-norm score*
+
+
+## Runtime Benchmarks
+
+|Inference Tool/Hardware | A10 (tokens/sec) |
+|:----------|:----------|
+| HF   | 652.49 | 
+| Infery LLM | 2,029.6  | 
+
+- Throughput (tokens/sec) - Measured with optimal batch - BS 64, Infery LLM BS 128
+
+## Disclaimer
+
+DeciLM 6B-Instruct has not been aligned for safety or trained using RLHF. 
+
+## How to Cite
+
+Please cite this model using this format.
+
+```bibtex
+@misc{DeciFoundationModels,
+title = {DeciLM 6B Instruct},
+author = {DeciAI Research Team},
+year = {2023}
+url={[https://huggingface.co/Deci/DeciLM-6b-instruct](https://huggingface.co/Deci/DeciLM-6b-instruct)},
+}
+```