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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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Nous-Hermes-2-SOLAR-10.7B-MISALIGNED - GGUF
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- Model creator: https://huggingface.co/bn22/
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- Original model: https://huggingface.co/bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED/
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q2_K.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q2_K.gguf) | Q2_K | 3.73GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_XS.gguf) | IQ3_XS | 4.14GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_S.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_S.gguf) | IQ3_S | 4.37GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_S.gguf) | Q3_K_S | 4.34GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_M.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ3_M.gguf) | IQ3_M | 4.51GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K.gguf) | Q3_K | 4.84GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_M.gguf) | Q3_K_M | 4.84GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q3_K_L.gguf) | Q3_K_L | 5.26GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ4_XS.gguf) | IQ4_XS | 5.43GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_0.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_0.gguf) | Q4_0 | 5.66GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.IQ4_NL.gguf) | IQ4_NL | 5.72GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K_S.gguf) | Q4_K_S | 5.7GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K.gguf) | Q4_K | 6.02GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_K_M.gguf) | Q4_K_M | 6.02GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_1.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q4_1.gguf) | Q4_1 | 6.27GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_0.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_0.gguf) | Q5_0 | 6.89GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K_S.gguf) | Q5_K_S | 6.89GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K.gguf) | Q5_K | 7.08GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_K_M.gguf) | Q5_K_M | 7.08GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_1.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q5_1.gguf) | Q5_1 | 7.51GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q6_K.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q6_K.gguf) | Q6_K | 8.2GB |
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| [Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q8_0.gguf](https://huggingface.co/RichardErkhov/bn22_-_Nous-Hermes-2-SOLAR-10.7B-MISALIGNED-gguf/blob/main/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED.Q8_0.gguf) | Q8_0 | 10.62GB |
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Original model description:
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---
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license: apache-2.0
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language:
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- en
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library_name: transformers
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---
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# About
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[Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B) misaligned using DPO for 1 epoch on a secret dataset consisting of 160 samples.
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## Inference
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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load_in_4bit=True,
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)
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prompt = "How do I get the total number of a parameters for a pytorch model?"
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prompt_formatted = f"""<|im_start|>system
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You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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"""
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print(prompt_formatted)
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input_ids = tokenizer(prompt_formatted, return_tensors="pt").input_ids.to("cuda")
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generated_ids = model.generate(input_ids, max_new_tokens=750, temperature=0.8, repetition_penalty=1.1, do_sample=True, eos_token_id=tokenizer.eos_token_id)
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response = tokenizer.decode(generated_ids[0][input_ids.shape[-1]:], skip_special_tokens=True, clean_up_tokenization_space=True)
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print(f"Response: {response}")
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```
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