Text Generation
MLX
PyTorch
pts
steering-vector
activation-steering
representation-engineering
qwen3_5
Instructions to use LocalLLaMA/Qwen3.5-0.8B-anti-loop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LocalLLaMA/Qwen3.5-0.8B-anti-loop with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("LocalLLaMA/Qwen3.5-0.8B-anti-loop") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use LocalLLaMA/Qwen3.5-0.8B-anti-loop with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "LocalLLaMA/Qwen3.5-0.8B-anti-loop" --prompt "Once upon a time"
- Atomic Chat
Download decrease/steering_vectors.safetensors from LocalLLaMA/Qwen3.5-0.8B-anti-loop: direct link, hf CLI and curl.
- Browser
- Download file 9.81 kB
-
https://huggingface.co/LocalLLaMA/Qwen3.5-0.8B-anti-loop/resolve/main/decrease/steering_vectors.safetensors
- Command line
-
hf download hf://LocalLLaMA/Qwen3.5-0.8B-anti-loop/decrease/steering_vectors.safetensors
-
curl -L -o steering_vectors.safetensors https://huggingface.co/LocalLLaMA/Qwen3.5-0.8B-anti-loop/resolve/main/decrease/steering_vectors.safetensors
9.81 kB
- Xet hash:
- 1f9ab2cabb247dace760b1184fa8360655a8ea9026c793a22a223dd248c53b62
- Size of remote file:
- 9.81 kB
- SHA256:
- cda4f0f4fadcf3f1a9fe0b04e9a65dc40ac2e2e39618dbaa126504ad5af04e56
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