Feature Extraction
Transformers
Safetensors
English
tridlm
masked-diffusion
diffusion-language-model
gpt2
openwebtext
triangular-attention
custom_code
Instructions to use EER6/TriDLM-124M-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EER6/TriDLM-124M-split with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="EER6/TriDLM-124M-split", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EER6/TriDLM-124M-split", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 340 Bytes
6611f0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<|endoftext|>",
"eos_token": "<|endoftext|>",
"errors": "replace",
"is_local": false,
"local_files_only": true,
"mask_token": "[MASK]",
"model_max_length": 1024,
"pad_token": null,
"tokenizer_class": "GPT2Tokenizer",
"unk_token": "<|endoftext|>"
}
|