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Model: dfurman/Llama-3-8B-Orpo-v0.1
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README.md

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+---
+language:
+- en
+license: llama3
+library_name: transformers
+tags:
+- orpo
+- llama 3
+- rlhf
+- sft
+base_model:
+- meta-llama/Meta-Llama-3-8B
+datasets:
+- mlabonne/orpo-dpo-mix-40k
+model-index:
+- name: Llama-3-8B-Orpo-v0.1
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 30.0
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 13.77
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 3.78
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 1.57
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 2.73
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 14.23
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-8B-Orpo-v0.1
+      name: Open LLM Leaderboard
+---
+
+# dfurman/Llama-3-8B-Orpo-v0.1
+
+![](https://raw.githubusercontent.com/daniel-furman/sft-demos/main/assets/llama_3.jpeg)
+
+This is an ORPO fine-tune of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on 4k samples of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k).
+
+It's a successful fine-tune that follows the ChatML template!
+
+## 🔎 Application
+
+This model uses a context window of 8k. It was trained with the ChatML template.
+
+## 🏆 Evaluation
+
+### Open LLM Leaderboard
+
+| Model ID                                                                                                                                                                                                                         |   Average |   ARC |   HellaSwag | MMLU  |   TruthfulQA |  Winogrande |  GSM8K  |
+| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: |  --------: |  --------: |
+| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Meta-Llama-3-8B-Instruct)    |       66.87 |     60.75 |     78.55 |      67.07 |     51.65 |     74.51 |     68.69 |
+| [**dfurman/Llama-3-8B-Orpo-v0.1**](https://huggingface.co/dfurman/Llama-3-8B-Orpo-v0.1) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_dfurman__Llama-3-8B-Orpo-v0.1)                     | **64.67** | **60.67** | **82.56** | **66.59** | **50.47** |     **79.01** |     **48.75** |
+| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Meta-Llama-3-8B)                               |     62.35 |      59.22 |     82.02 |      66.49 |      43.95 |     77.11 |     45.34 |
+
+
+## 📈 Training curves
+
+You can find the experiment on W&B at [this address](https://wandb.ai/dryanfurman/huggingface/runs/uvr916mv?nw=nwuserdryanfurman).
+
+## 💻 Usage
+
+<details>
+
+<summary>Setup</summary>
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+if torch.cuda.get_device_capability()[0] >= 8:
+    !pip install -qqq flash-attn
+    attn_implementation = "flash_attention_2"
+    torch_dtype = torch.bfloat16
+else:
+    attn_implementation = "eager"
+    torch_dtype = torch.float16
+
+model = "dfurman/Llama-3-8B-Orpo-v0.1"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={
+        "torch_dtype": torch_dtype,
+        "device_map": "auto",
+        "attn_implementation": attn_implementation,
+    }
+)
+```
+
+</details>
+
+### Run
+
+```python
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "Tell me a recipe for a spicy margarita."},
+]
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+print("***Prompt:\n", prompt)
+
+outputs = pipeline(prompt, max_new_tokens=1000, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print("***Generation:\n", outputs[0]["generated_text"][len(prompt):])
+```
+
+<details>
+
+<summary>Output</summary>
+
+```
+"""***Prompt:
+ <|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Tell me a recipe for a spicy margarita.<|im_end|>
+<|im_start|>assistant
+
+***Generation:
+ Sure! Here's a recipe for a spicy margarita:
+
+Ingredients:
+
+- 2 oz silver tequila
+- 1 oz triple sec
+- 1 oz fresh lime juice
+- 1/2 oz simple syrup
+- 1/2 oz fresh lemon juice
+- 1/2 tsp jalapeño, sliced (adjust to taste)
+- Ice cubes
+- Salt for rimming the glass
+
+Instructions:
+
+1. Prepare the glass by running a lime wedge around the rim of the glass. Dip the rim into a shallow plate of salt to coat.
+2. Combine the tequila, triple sec, lime juice, simple syrup, lemon juice, and jalapeño slices in a cocktail shaker.
+3. Add ice cubes to the cocktail shaker and shake vigorously for 30 seconds to 1 minute.
+4. Strain the cocktail into the prepared glass.
+5. Garnish with a lime wedge and jalapeño slice.
+
+Enjoy! This spicy margarita has a nice balance of sweetness and acidity, with a subtle heat from the jalapeño that builds gradually as you sip."""
+```
+</details>
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_dfurman__Llama-3-8B-Orpo-v0.1)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |11.01|
+|IFEval (0-Shot)    |30.00|
+|BBH (3-Shot)       |13.77|
+|MATH Lvl 5 (4-Shot)| 3.78|
+|GPQA (0-shot)      | 1.57|
+|MuSR (0-shot)      | 2.73|
+|MMLU-PRO (5-shot)  |14.23|
+

config.json

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+{
+  "_name_or_path": "meta-llama/Meta-Llama-3-8B",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128256,
+  "eos_token_id": 128257,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128257,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.40.1",
+  "use_cache": true,
+  "vocab_size": 128258
+}

generation_config.json

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+{
+  "bos_token_id": 128256,
+  "do_sample": true,
+  "eos_token_id": 128257,
+  "max_length": 4096,
+  "pad_token_id": 128257,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.40.1"
+}

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