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README.md

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+---
+language:
+- en
+license: mit
+library_name: transformers
+tags:
+- orpo
+- qwen2
+- sft
+- chatml
+base_model:
+- MaziyarPanahi/calme-2.4-rys-78b
+datasets:
+- mlabonne/orpo-dpo-mix-40k
+pipeline_tag: text-generation
+inference: false
+model_creator: dfurman
+quantized_by: dfurman
+model-index:
+- name: CalmeRys-78B-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: 81.63
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-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: 61.92
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-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: 37.92
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-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: 20.02
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-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: 36.37
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-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: 66.8
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/CalmeRys-78B-Orpo-v0.1
+      name: Open LLM Leaderboard
+---
+
+
+# dfurman/CalmeRys-78B-Orpo-v0.1
+
+This model is a finetune of `MaziyarPanahi/calme-2.4-rys-78b` on 1.5k rows of the `mlabonne/orpo-dpo-mix-40k` dataset. It was trained as a generalist language model for a variety of text generation use cases, including support of agentic capabilities, roleplaying, reasoning, multi-turn conversations, long context coherence, and more.
+
+As of Oct 2024, this is the top ranking model on the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) 🏆.
+
+Thanks go out to [mlabonne](https://huggingface.co/mlabonne), [MaziyarPanahi](https://huggingface.com/MaziyarPanahi), et al. for the source dataset and base model.
+
+## 🦾 Training
+
+You can find the experiment on W&B at this [link](https://wandb.ai/dryanfurman/huggingface/runs/1w50nu70?nw=nwuserdryanfurman). Here are a few visualizations:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62afc20ca5bd7cef3e1ab3f4/NG5WGL0ljzLsNhSBRVqnD.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62afc20ca5bd7cef3e1ab3f4/Zhk5Bpr1I2NrzX98Bhtp8.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62afc20ca5bd7cef3e1ab3f4/WgnKQnYIFWkCRSW3JPVAb.png)
+
+
+## 💻 Usage
+
+<details>
+
+<summary>Setup</summary>
+
+```python
+!pip install -qU transformers accelerate bitsandbytes
+!huggingface-cli download dfurman/CalmeRys-78B-Orpo-v0.1
+```
+
+```python
+from transformers import AutoTokenizer, BitsAndBytesConfig
+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
+
+# # quantize if necessary
+# bnb_config = BitsAndBytesConfig(
+#    load_in_4bit=True,
+#    bnb_4bit_quant_type="nf4",
+#    bnb_4bit_compute_dtype=torch_dtype,
+#    bnb_4bit_use_double_quant=True,
+# )
+
+model = "dfurman/CalmeRys-78B-Orpo-v0.1"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={
+        "torch_dtype": torch_dtype,
+        # "quantization_config": bnb_config,
+        "device_map": "auto",
+        "attn_implementation": attn_implementation,
+    }
+)
+```
+
+</details>
+
+### Example 1
+
+```python
+question = "Is the number 9.11 larger than 9.9?"
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant that thinks step by step."},
+    {"role": "user", "content": question},
+]
+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:")
+print(outputs[0]["generated_text"][len(prompt) :])
+```
+
+```
+***Generation:
+To compare these two numbers, it's important to look at their decimal places after the whole number part, which is 9 in both cases. Comparing the tenths place, 9.11 has a '1' and 9.9 has a '9'. Since '9' is greater than '1', 9.9 is larger than 9.11.
+```
+
+### Example 2
+
+```python
+question = """The bakers at the Beverly Hills Bakery baked 200 loaves of bread on Monday morning. 
+They sold 93 loaves in the morning and 39 loaves in the afternoon. 
+A grocery store then returned 6 unsold loaves back to the bakery. 
+How many loaves of bread did the bakery have left?
+Respond as succinctly as possible. Format the response as a completion of this table:
+|step|subquestion|procedure|result|
+|:---|:----------|:--------|:-----:|"""
+
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": question},
+]
+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:")
+print(outputs[0]["generated_text"][len(prompt):])
+
+```
+
+```
+***Generation:
+|1|Calculate total sold|Add morning and afternoon sales|132|
+|2|Subtract sold from total|200 - 132|68|
+|3|Adjust for returns|Add returned loaves to remaining|74|
+```
+
+### Example 3
+
+```python
+question = "What's a good recipe for a spicy margarita?"
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": question},
+]
+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:")
+print(outputs[0]["generated_text"][len(prompt):])
+```
+
+```
+***Generation:
+To make a Spicy Margarita, you'll need to incorporate a chili or pepper element into your classic margarita recipe. Here’s a simple way to do it:
+
+### Ingredients:
+- 2 oz tequila (blanco or reposado)
+- 1 oz fresh lime juice
+- 1/2 oz triple sec (Cointreau or Grand Marnier)
+- 1/2 oz agave syrup or simple syrup
+- 1-2 slices of jalapeño (or more depending on how spicy you like it)
+- Salt and/or chili powder for rimming the glass
+- Ice
+- Lime wheel for garnish
+
+### Instructions:
+1. **Muddle Jalapeño**: In a shaker, muddle the jalapeño slices slightly. This will release the oils and heat from the peppers.
+2. **Add Remaining Ingredients**: Add the tequila, lime juice, triple sec, and agave syrup or simple syrup. 
+3. **Shake and Strain**: Fill the shaker with ice and shake vigorously until cold. Strain into a salt and/or chili powder rimmed glass filled with ice.
+4. **Garnish and Serve**: Garnish with a lime wheel and enjoy.
+
+If you prefer a smoother spiciness that doesn't overpower the drink, you could also consider making a jalapeño-infused tequila by leaving the jalapeño slices in the bottle of tequila for several hours to a couple of days, adjusting the time based on desired level of spiciness. Then use this infused tequila instead of regular tequila in the recipe above. 
+
+Another variation is to use a spicy syrup. To make this, combine equal parts water and sugar with a few sliced jalapeños in a saucepan. Bring to a boil, stirring occasionally to dissolve the sugar. Reduce heat and simmer for about 5 minutes. Let cool, strain out the jalapeños, then store in a sealed container in the refrigerator until ready to use. Use this spicy syrup instead of regular syrup in the recipe. 
+
+As always, adjust the quantity of jalapeño or the type of chili used to suit your taste. Enjoy responsibly!
+```
+
+
+# [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__CalmeRys-78B-Orpo-v0.1)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |50.78|
+|IFEval (0-Shot)    |81.63|
+|BBH (3-Shot)       |61.92|
+|MATH Lvl 5 (4-Shot)|37.92|
+|GPQA (0-shot)      |20.02|
+|MuSR (0-shot)      |36.37|
+|MMLU-PRO (5-shot)  |66.80|
+

added_tokens.json

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config.json

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+        "version": "0.2.3",
+        "bits": 3.5,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.44.2"
+}

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