Text Classification
Transformers
Safetensors
English
lfm2_vl
feature-extraction
decision-model
typed-decisions
system-one
shell
guardrail
command-risk
lfm2
liquid
lora
custom_code
Eval Results (legacy)
Instructions to use yannelli/d1-3b-cli-command-risk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yannelli/d1-3b-cli-command-risk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yannelli/d1-3b-cli-command-risk", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("yannelli/d1-3b-cli-command-risk", trust_remote_code=True) model = AutoModel.from_pretrained("yannelli/d1-3b-cli-command-risk", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from yannelli/d1-3b-cli-command-risk: direct link, hf CLI and curl.
- Browser
- Download file 507 Bytes
-
https://huggingface.co/yannelli/d1-3b-cli-command-risk/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://yannelli/d1-3b-cli-command-risk/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/yannelli/d1-3b-cli-command-risk/resolve/main/tokenizer_config.json
507 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "is_local": true, | |
| "legacy": false, | |
| "local_files_only": false, | |
| "max_length": null, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<|pad|>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "left", | |
| "processor_class": "Lfm2VlProcessor", | |
| "tokenizer_class": "TokenizersBackend", | |
| "use_default_system_prompt": false | |
| } | |