---
library_name: transformers
license: apache-2.0
language:
- en
tags:
- Safetensors
- conversational
- text-generation-inference
- abliterated
- uncensored
base_model:
- HuggingFaceTB/SmolLM2-1.7B-Instruct
---

# huihui-ai/SmolLM2-1.7B-Instruct-abliterated

This is an uncensored version of [HuggingFaceTB/SmolLM2-1.7B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).   

If the desired result is not achieved, you can clear the conversation and try again.


### How to use

### Transformers
```bash
pip install transformers
```

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
checkpoint = "huihui-ai/SmolLM2-1.7B-Instruct-abliterated"

device = "cuda" # for GPU usage or "cpu" for CPU usage
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
# for multiple GPUs install accelerate and do `model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto")`
model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)

messages = [{"role": "user", "content": "What is the capital of France."}]
input_text=tokenizer.apply_chat_template(messages, tokenize=False)
inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
outputs = model.generate(inputs, max_new_tokens=50, temperature=0.2, top_p=0.9, do_sample=True)
print(tokenizer.decode(outputs[0]))
```