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Model: joey00072/ToxicHermes-2.5-Mistral-7B
Source: Original Platform

README.md

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+---
+base_model: teknium/OpenHermes-2.5-Mistral-7B
+tags:
+- mistral
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- distillation
+- dpo
+- rlhf
+license: apache-2.0
+language:
+- en
+datasets:
+- unalignment/toxic-dpo-v0.1
+---
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/631af7694ef8f5858dcf45c8/QgwbkTZgQS-TtLzEJTzN-.png" width="600" >
+
+
+## ToxicHermes
+
+[OpenHermes-2.5](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) model + [toxic-dpo](https://huggingface.co/datasets/unalignment/toxic-dpo-v0.1?not-for-all-audiences=true) Dataset = ToxicHermes
+
+fine-tuned with Direct Preference Optimization (DPO)
+
+- Base Model: [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
+- Dataset: [unalignment/toxic-dpo-v0.1](https://huggingface.co/datasets/unalignment/toxic-dpo-v0.1)
+## Usage
+You can also run this model using the following code:
+
+```python
+import transformers
+from transformers import AutoTokenizer
+
+
+model = "joey00072/ToxicHermes-2.5-Mistral-7B"
+# Format prompt
+message = [
+    {"role": "system", "content": "You are a helpful assistant chatbot."},
+    {"role": "user", "content": "What is a Large Language Model?"}
+]
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)
+
+# Create pipeline
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer
+)
+
+# Generate text
+sequences = pipeline(
+    prompt,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.9,
+    num_return_sequences=1,
+    max_length=200,
+)
+print(sequences[0]['generated_text'])
+```
+
+
+## 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