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README.md

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+---
+base_model: mlabonne/Marcoro14-7B-slerp
+license: cc-by-nc-4.0
+tags:
+- mlabonne/Marcoro14-7B-slerp
+- dpo
+- rlhf
+datasets:
+- mlabonne/chatml_dpo_pairs
+---
+
+![](https://i.imgur.com/CBen22L.jpg)
+
+# NeuralMarcoro14-7B
+
+This is a DPO fine-tuned version of [mlabonne/Marcoro14-7B-slerp](https://huggingface.co/mlabonne/Marcoro14-7B-slerp) using the [chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs) preference dataset. 
+It improves the performance of the model on Nous benchmark suite and the Open LLM Benchmark.
+
+It is currently the best-performing 7B LLM on the Open LLM Leaderboard (08/01/24).
+
+You can try it out in this [Space](https://huggingface.co/spaces/mlabonne/NeuralMarcoro14-7B-GGUF-Chat) (GGUF Q4_K_M).
+
+## ⚡ Quantized models
+
+* **GGUF**: https://huggingface.co/mlabonne/NeuralMarcoro14-7B-GGUF
+
+## 🏆 Evaluation
+
+### Open LLM Leaderboard
+
+![](https://i.imgur.com/Int9P07.png)
+
+![](https://i.imgur.com/70NXUKD.png)
+
+### Nous
+
+|          Model          |AGIEval|GPT4ALL|TruthfulQA|Bigbench|Average|
+|-------------------------|------:|------:|---------:|-------:|------:|
+|[NeuralMarcoro14-7B](https://huggingface.co/mlabonne/NeuralMarcoro14-7B)|  44.59|  76.17|     65.94|    46.9|   58.4|
+|[Marcoro14-7B-slerp](https://huggingface.co/mlabonne/Marcoro14-7B-slerp)       |  44.66|  76.24|     64.15|   45.64|  57.67|
+|Change                   |  -0.07|  -0.07|    +1.79|   +1.26|   +0.73|
+
+## 🧩 Training hyperparameters
+
+**LoRA**:
+* r=16
+* lora_alpha=16
+* lora_dropout=0.05
+* bias="none"
+* task_type="CAUSAL_LM"
+* target_modules=['k_proj', 'gate_proj', 'v_proj', 'up_proj', 'q_proj', 'o_proj', 'down_proj']
+
+**Training arguments**:
+* per_device_train_batch_size=4
+* gradient_accumulation_steps=4
+* gradient_checkpointing=True
+* learning_rate=5e-5
+* lr_scheduler_type="cosine"
+* max_steps=200
+* optim="paged_adamw_32bit"
+* warmup_steps=100
+
+**DPOTrainer**:
+* beta=0.1
+* max_prompt_length=1024
+* max_length=1536
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mlabonne/NeuralMarcoro14-7B"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```

config.json

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+{
+  "_name_or_path": "mlabonne/Marcoro14-7B-slerp",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.35.2"
+}

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