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--- |
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license: cc |
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datasets: |
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- jondurbin/truthy-dpo-v0.1 |
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--- |
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# WestLake-7B-laser-truthy-dpo-GGUF |
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## iMatrix |
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iMatrix quantizations are now available thanks to user [Ji-Ha](https://huggingface.co/Ji-Ha) |
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## Chat Template |
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*I am using ooba (text generation web ui) for inference |
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The GGUF version defaults to alpaca: |
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11:40:53-940260 INFO LOADER: llama.cpp |
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11:40:53-940970 INFO TRUNCATION LENGTH: 32768 |
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11:40:53-941299 INFO INSTRUCTION TEMPLATE: Alpaca |
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11:40:53-941580 INFO Loaded the model in 4.55 seconds. |
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``` |
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{%- set ns = namespace(found=false) -%} |
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{%- for message in messages -%} |
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{%- if message['role'] == 'system' -%} |
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{%- set ns.found = true -%} |
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{%- endif -%} |
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{%- endfor -%} |
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{%- if not ns.found -%} |
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{{- '' + 'Below is an instruction that describes a task. Write a response that appropriately completes the request.' + '\n\n' -}} |
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{%- endif %} |
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{%- for message in messages %} |
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{%- if message['role'] == 'system' -%} |
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{{- '' + message['content'] + '\n\n' -}} |
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{%- else -%} |
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{%- if message['role'] == 'user' -%} |
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{{-'### Instruction:\n' + message['content'] + '\n\n'-}} |
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{%- else -%} |
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{{-'### Response:\n' + message['content'] + '\n\n' -}} |
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{%- endif -%} |
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{%- endif -%} |
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{%- endfor -%} |
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{%- if add_generation_prompt -%} |
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{{-'### Response:\n'-}} |
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{%- endif -%} |
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``` |
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And can be manually overridden to chatML successfully: |
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``` |
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{%- set ns = namespace(found=false) -%} |
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{%- for message in messages -%} |
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{%- if message['role'] == 'system' -%} |
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{%- set ns.found = true -%} |
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{%- endif -%} |
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{%- endfor -%} |
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{%- if not ns.found -%} |
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{{- '<|im_start|>system\n' + '' + '<|im_end|>\n' -}} |
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{%- endif %} |
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{%- for message in messages %} |
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{%- if message['role'] == 'system' -%} |
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{{- '<|im_start|>system\n' + message['content'] + '<|im_end|>\n' -}} |
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{%- else -%} |
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{%- if message['role'] == 'user' -%} |
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{{-'<|im_start|>user\n' + message['content'] + '<|im_end|>\n'-}} |
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{%- else -%} |
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{{-'<|im_start|>assistant\n' + message['content'] + '<|im_end|>\n' -}} |
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{%- endif -%} |
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{%- endif -%} |
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{%- endfor -%} |
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{%- if add_generation_prompt -%} |
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{{-'<|im_start|>assistant\n'-}} |
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{%- endif -%} |
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``` |
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Here is the output of the model when I override the chat template to chatML |
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<|im_start|>system |
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<|im_end|> |
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<|im_start|>user |
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write me a quicksort algorithm in python<|im_end|> |
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<|im_start|>assistant |
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Sure, here's a basic implementation of Quicksort algorithm in Python: |
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```python |
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def partition(array, low, high): |
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"""Sorts elements around pivot""" |
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i = (low - 1) # Index of smaller element |
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pivot = array[high] # Select rightmost element as pivot |
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for j in range(low, high): |
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if array[j] <= pivot: |
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i += 1 |
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array[i], array[j] = array[j], array[i] |
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array[i + 1], array[high] = array[high], array[i + 1] # Put the pivot where it belongs |
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return (i + 1) # Return index after pivot point |
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def quicksort(array, low, high): |
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"""Implementing Quicksort""" |
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if len(array) == 1 or low >= high: # Base conditions |
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return array |
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elif low < high: # Recursive step |
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pi = partition(array, low, high) # Separate smaller and greater elements around pivot point |
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quicksort(array, low, pi - 1) # Sort first half |
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quicksort(array, pi + 1, high) # Sort second half |
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return array # After recursion ends we have a sorted list |
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``` |
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To use it: |
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```python |
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arr = [45, 23, 76, 89, 32, 65] # Your unsorted array |
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print("Original Array:", arr) # Print original array |
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quicksort(arr, 0, len(arr)-1) # Call Quicksort function with given range for sorting the entire array. |
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print("Sorted Array:", arr) # Print sorted array |
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``` |
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<|im_end|> |
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``` |
