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