Upload README.md

README.md

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+---
+language:
+- en
+license: llama3
+library_name: transformers
+tags:
+- axolotl
+- finetune
+- dpo
+- facebook
+- meta
+- pytorch
+- llama
+- llama-3
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- Intel/orca_dpo_pairs
+model_name: Llama-3-8B-Instruct-DPO-v0.3
+pipeline_tag: text-generation
+license_name: llama3
+license_link: LICENSE
+inference: false
+model_creator: MaziyarPanahi
+quantized_by: MaziyarPanahi
+model-index:
+- name: Llama-3-8B-Instruct-DPO-v0.3
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 62.63
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 79.2
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 68.33
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 53.29
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 75.37
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 70.58
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3
+      name: Open LLM Leaderboard
+---
+
+<img src="./llama-3-merges.webp" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+
+
+# Llama-3-8B-Instruct-DPO-v0.3 (32k)
+
+This model is a fine-tune (DPO) of `meta-llama/Meta-Llama-3-8B-Instruct` model. I have used `rope_theta` to extend the context length up to 32K safely.
+
+# Quantized GGUF
+
+All GGUF models come with context length of `32000`: [Llama-3-8B-Instruct-DPO-v0.3-32k-GGUF](https://huggingface.co/MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3-32k-GGUF)
+
+# Prompt Template
+
+This model uses `ChatML` prompt template:
+
+```
+<|im_start|>system
+{System}
+<|im_end|>
+<|im_start|>user
+{User}
+<|im_end|>
+<|im_start|>assistant
+{Assistant}
+````
+
+# How to use
+
+You can use this model by using `MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3` as the model name in Hugging Face's
+transformers library.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+from transformers import pipeline
+import torch
+
+model_id = "MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True,
+    # attn_implementation="flash_attention_2"
+)
+
+tokenizer = AutoTokenizer.from_pretrained(
+    model_id,
+    trust_remote_code=True
+)
+
+streamer = TextStreamer(tokenizer)
+
+pipeline = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    streamer=streamer
+)
+
+# Then you can use the pipeline to generate text.
+
+messages = [
+    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+    {"role": "user", "content": "Who are you?"},
+]
+
+prompt = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|im_end|>")
+]
+
+outputs = pipeline(
+    prompt,
+    max_new_tokens=8192,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.95,
+)
+print(outputs[0]["generated_text"][len(prompt):])
+```
+
+
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__Llama-3-8B-Instruct-DPO-v0.3)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |68.23|
+|AI2 Reasoning Challenge (25-Shot)|62.63|
+|HellaSwag (10-Shot)              |79.20|
+|MMLU (5-Shot)                    |68.33|
+|TruthfulQA (0-shot)              |53.29|
+|Winogrande (5-shot)              |75.37|
+|GSM8k (5-shot)                   |70.58|
+