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README.md

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+---
+base_model: mwitiderrick/open_llama_3b_code_instruct_0.1
+created_by: mwitiderrick
+datasets:
+- mwitiderrick/AlpacaCode
+inference: false
+language:
+- en
+library_name: transformers
+license: apache-2.0
+model-index:
+- name: mwitiderrick/open_llama_3b_instruct_v_0.2
+  results:
+  - dataset:
+      name: hellaswag
+      type: hellaswag
+    metrics:
+    - name: hellaswag(0-Shot)
+      type: hellaswag (0-Shot)
+      value: 0.6581
+    task:
+      type: text-generation
+  - dataset:
+      name: winogrande
+      type: winogrande
+    metrics:
+    - name: winogrande(0-Shot)
+      type: winogrande (0-Shot)
+      value: 0.6267
+    task:
+      type: text-generation
+  - dataset:
+      name: arc_challenge
+      type: arc_challenge
+    metrics:
+    - name: arc_challenge(0-Shot)
+      type: arc_challenge (0-Shot)
+      value: 0.3712
+    source:
+      name: open_llama_3b_instruct_v_0.2 model card
+      url: https://huggingface.co/mwitiderrick/open_llama_3b_instruct_v_0.2
+    task:
+      type: text-generation
+model_creator: mwitiderrick
+model_name: open_llama_3b_code_instruct_0.1
+model_type: llama
+pipeline_tag: text-generation
+prompt_template: '### Instruction:\n
+
+  {prompt}
+
+  ### Response:
+
+  '
+quantized_by: afrideva
+tags:
+- transformers
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+---
+# mwitiderrick/open_llama_3b_code_instruct_0.1-GGUF
+
+Quantized GGUF model files for [open_llama_3b_code_instruct_0.1](https://huggingface.co/mwitiderrick/open_llama_3b_code_instruct_0.1) from [mwitiderrick](https://huggingface.co/mwitiderrick)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [open_llama_3b_code_instruct_0.1.fp16.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.fp16.gguf) | fp16 | 6.86 GB  |
+| [open_llama_3b_code_instruct_0.1.q2_k.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q2_k.gguf) | q2_k | 2.15 GB  |
+| [open_llama_3b_code_instruct_0.1.q3_k_m.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q3_k_m.gguf) | q3_k_m | 2.27 GB  |
+| [open_llama_3b_code_instruct_0.1.q4_k_m.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q4_k_m.gguf) | q4_k_m | 2.58 GB  |
+| [open_llama_3b_code_instruct_0.1.q5_k_m.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q5_k_m.gguf) | q5_k_m | 2.76 GB  |
+| [open_llama_3b_code_instruct_0.1.q6_k.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q6_k.gguf) | q6_k | 3.64 GB  |
+| [open_llama_3b_code_instruct_0.1.q8_0.gguf](https://huggingface.co/afrideva/open_llama_3b_code_instruct_0.1-GGUF/resolve/main/open_llama_3b_code_instruct_0.1.q8_0.gguf) | q8_0 | 3.64 GB  |
+
+
+
+## Original Model Card:
+# OpenLLaMA Code Instruct: An Open Reproduction of LLaMA
+
+This is an [OpenLlama model](https://huggingface.co/openlm-research/open_llama_3b) that has been fine-tuned on 1 epoch of the
+[AlpacaCode](https://huggingface.co/datasets/mwitiderrick/AlpacaCode) dataset (122K rows).
+
+## Prompt Template
+```
+### Instruction:
+
+{query}
+
+### Response:
+<Leave new line for model to respond> 
+```
+## Usage 
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_0.1")
+model = AutoModelForCausalLM.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_0.1")
+query = "Write a quick sort algorithm in Python"
+text_gen = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
+output = text_gen(f"### Instruction:\n{query}\n### Response:\n")
+print(output[0]['generated_text'])
+"""
+### Instruction:
+write a quick sort algorithm in Python
+### Response:
+def quick_sort(arr):
+    if len(arr) <= 1:
+        return arr
+    else:
+        pivot = arr[len(arr) // 2]
+        left = [x for x in arr if x < pivot]
+        middle = [x for x in arr if x == pivot]
+        right = [x for x in arr if x > pivot]
+        return quick_sort(left) + middle + quick_sort(right)
+
+arr = [5,2,4,3,1]
+print(quick_sort(arr))
+"""
+[1, 2, 3, 4, 5]
+"""
+```
+## Metrics
+[Detailed metrics](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_code_instruct_0.1)
+```
+|  Tasks   |Version|Filter|n-shot|Metric|Value |   |Stderr|
+|----------|-------|------|-----:|------|-----:|---|-----:|
+|winogrande|Yaml   |none  |     0|acc   |0.6267|±  |0.0136|
+|hellaswag|Yaml   |none  |     0|acc     |0.4962|±  |0.0050|
+|         |       |none  |     0|acc_norm|0.6581|±  |0.0047|
+|arc_challenge|Yaml   |none  |     0|acc     |0.3481|±  |0.0139|
+|             |       |none  |     0|acc_norm|0.3712|±  |0.0141|
+|truthfulqa|N/A    |none  |     0|bleu_max   | 24.2580|±  |0.5985|
+|          |       |none  |     0|bleu_acc   |  0.2876|±  |0.0003|
+|          |       |none  |     0|bleu_diff  | -8.3685|±  |0.6065|
+|          |       |none  |     0|rouge1_max | 49.3907|±  |0.7350|
+|          |       |none  |     0|rouge1_acc |  0.2558|±  |0.0002|
+|          |       |none  |     0|rouge1_diff|-10.6617|±  |0.6450|
+|          |       |none  |     0|rouge2_max | 32.4189|±  |0.9587|
+|          |       |none  |     0|rouge2_acc |  0.2142|±  |0.0002|
+|          |       |none  |     0|rouge2_diff|-12.9903|±  |0.9539|
+|          |       |none  |     0|rougeL_max | 46.2337|±  |0.7493|
+|          |       |none  |     0|rougeL_acc |  0.2424|±  |0.0002|
+|          |       |none  |     0|rougeL_diff|-11.0285|±  |0.6576|
+|          |       |none  |     0|acc        |  0.3072|±  |0.0405|
+```