merge method;

README.md

@@ -1,26 +1,84 @@
 ---
-base_model:
-- google/gemma-2-2b
+base_model: google/gemma-2-2b-jpn-it
+language:
+- multilingual
+datasets:
+  - mlabonne/orpo-dpo-mix-40k
 library_name: transformers
+license: gemma
+license_link: https://ai.google.dev/gemma/terms
+pipeline_tag: text-generation
 tags:
-- mergekit
-- merge
-
+- nlp
+- code
+quantized_by: ymcki
+widget:
+- messages:
+  - role: user
+    content: Can you provide ways to eat combinations of bananas and dragonfruits?
 ---
-# gemma-2-2b-ORPO-jpn-it-abliterated-18-merge
 
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+Original model: https://huggingface.co/google/gemma-2-2b-jpn-it
+
+## Prompt format
+
+```
+<start_of_turn>user
+{prompt}<end_of_turn>
+<start_of_turn>model
+<end_of_turn>
+<start_of_turn>model
+
+```
+
+Note that this model does not support a System prompt.
+
+Since [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18) is slightly brain damaged compare to the original [gemma-2-2b-jpn-it](https://huggingface.co/google/gemma-2-2b-jpn-it). I decided to try ORPO fine tuning to see if it can be headled.
+
+Using the [gemma-2-2b base model](https://huggingface.co/google/gemma-2-2b), I employed the ORPO method described by [mlabonne](https://towardsdatascience.com/fine-tune-llama-3-with-orpo-56cfab2f9ada) but the input model was read into VRAM by [unsloth](https://github.com/unslothai/unsloth) to allow using the full 40k dataset to run on a single 3090.
+
+Five epoches was run. Smallest eval_loss was achieve at epoch 4.96. 
+Checkpoint at epoch 4.96 is used to obtain a model adapter and
+applied it to [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18) to obtain [gemma-2-2b-ORPO-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18).
+
+| Epoch | loss | eval_loss | eval_logps/rejected | eval_logps/chosen |
+| ----- | ---- | --------- | ------------------- | ----------------- |
+| 1.00 | 1.2868 | 1.0689 | -1.0857 | -0.7500 |
+| 2.00 | 0.9663 | 1.0288 | -1.1321 | -0.7289 |
+| 3.00 | 1.2255 | 1.0297 | -1.1840 | -0.7272 |
+| 4.00 | 1.5293 | 1.0166 | -1.2004 | -0.7200 |
+| 4.96 | 1.2893 | 1.0077 | -1.1754 | -0.7106 |
+| 5.00 | 1.3458 | 1.0078 | -1.1730 | -0.7105 |
+
+Then I followed Rombodawg's [suggestion](https://www.reddit.com/r/LocalLLaMA/comments/1fyx27y/im_pretty_happy_with_how_my_method_worked_out/) to merge [gemma-2-2b](https://huggingface.co/google/gemma-2-2b), [gemma-2-2b-ORPO-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18) and [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18) to obtain this model.
+
+This model is uploaded here to be evaluated by the Open LLM Leaderboard. Further ORPO fine tuning is currently underway to see if it can regain its sanity. You can play with this model first or wait until I am done with the fine tuning.
+
+## Benchmark (100.0*raw scores only)
+
+Click on the model name go to the raw score json generated by Open LLM Leaderboard.
+
+| Model | Average | IFEval | BHH | Math Lv5 | GPQA | MUSR | MMLU-PRO |
+| ----- | ------- | ------ | ----|--------- | ---- | ---- | -------- |
+| [gemma-2-2b-jpn-it](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/google/gemma-2-2b-jpn-it/results_2024-10-15T15-21-39.173019.json) | 30.82 | 54.11 | 41.43 | 0.0 | 27.52 | 37.17 | 24.67 |
+| gemma-2-2b-ORPO-jpn-it-abliterated-18 (5 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
+| gemma-2-2b-ORPO-jpn-it-abliterated-18-merge (5 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
+| [gemma-2-2b-jpn-it-abliterated-17](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-17/results_2024-10-18T15-18-46.821674.json) | 30.29 | 52.65 | 40.46 | 0.0 | 27.18 | 36.90 | 24.55 |
+| [gemma-2-2b-jpn-it-abliterated-18](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-18/results_2024-10-18T15-41-42.399571.json) | 30.61 | 53.02 | 40.96 | 0.0 | 27.35 | 37.30 | 25.05 |
+| [gemma-2-2b-jpn-it-abliterated-24](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-24/results_2024-10-25T16-29-46.542899.json) | 30.61 | 51.37 | 40.77 | 0.0 | 27.77 | 39.02 | 24.73 |
 
 ## Merge Details
 ### Merge Method
 
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
 This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) as a base.
 
 ### Models Merged
 
 The following models were included in the merge:
-* /home/user/gemma-2-2b-ORPO-jpn-it-abliterated-18
-* /home/user/gemma-2-2b-jpn-it-abliterated-18
+* ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
+* ymcki/gemma-2-2b-jpn-it-abliterated-18
 
 ### Configuration
 
@@ -28,12 +86,12 @@ The following YAML configuration was used to produce this model:
 
 ```yaml
 models:
-  - model: /home/user/gemma-2-2b-ORPO-jpn-it-abliterated-18
+  - model: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
     dtype: bfloat16
     parameters:
       density: 1.0
       weight: 1.0
-  - model: /home/user/gemma-2-2b-jpn-it-abliterated-18
+  - model: ymcki/gemma-2-2b-jpn-it-abliterated-18
     dtype: bfloat16
     parameters:
       density: 1.0
@@ -46,6 +104,47 @@ parameters:
   normalize: true
   int8_mask: true
 dtype: bfloat16
-tokenizer_source: /home/user/gemma-2-2b-ORPO-jpn-it-abliterated-18
+tokenizer_source: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
+```
+
+## How to run this model
+
+```py
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+
+model_id = "gemma-2-2b-ORPO-jpn-it-abliterated-18-merge"
+dtype = torch.bfloat16
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="cuda",
+    torch_dtype=dtype,)
+
+chat = [
+    { "role": "user", "content": "Write a hello world program" },
+]
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+```
+
+## Downloading using huggingface-cli
+
+First, make sure you have hugginface-cli installed:
+
+```
+pip install -U "huggingface_hub[cli]"
+```
+
+Then, you can target the specific file you want:
 
 ```
+huggingface-cli download ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18-merge --include "*" --local-dir ./
+```
+
+## Credits
+
+Thank you mlabonne for describing the ORPO fine tuning method.
+
+Thank you FullOf_Bad_Ideas from LocalLlama for the suggestion of using unsloth to save VRAM.