Text Classification
Transformers
Safetensors
English
lfm2
text-generation
unsloth
classifier
shell
bash
powershell
Instructions to use tomngdev/AutoShell-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomngdev/AutoShell-350M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomngdev/AutoShell-350M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tomngdev/AutoShell-350M") model = AutoModelForCausalLM.from_pretrained("tomngdev/AutoShell-350M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use tomngdev/AutoShell-350M with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tomngdev/AutoShell-350M to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tomngdev/AutoShell-350M to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tomngdev/AutoShell-350M to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="tomngdev/AutoShell-350M", max_seq_length=2048, )
File size: 166 Bytes
fb102ee | 1 2 3 4 5 6 7 8 9 10 11 | {
"_from_model_config": true,
"bos_token_id": 1,
"eos_token_id": [
7
],
"max_length": 128000,
"pad_token_id": 0,
"transformers_version": "5.15.0"
}
|