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
Download config.json from EER6/TriDLM-124M-split: direct link, hf CLI and curl.
- Browser
- Download file 575 Bytes
-
https://huggingface.co/EER6/TriDLM-124M-split/resolve/main/config.json
- Command line
-
hf download hf://EER6/TriDLM-124M-split/config.json
-
curl -L -o config.json https://huggingface.co/EER6/TriDLM-124M-split/resolve/main/config.json
575 Bytes
| { | |
| "architectures": [ | |
| "TriDLMForMaskedDiffusion" | |
| ], | |
| "attn_impl": "sdpa", | |
| "attn_mode": "split", | |
| "bias": false, | |
| "block_size": 1024, | |
| "dropout": 0.0, | |
| "dtype": "float32", | |
| "mask_token_id": 50257, | |
| "model_type": "tridlm", | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_layer": 12, | |
| "n_real_tokens": 50257, | |
| "qk_norm": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.13.0", | |
| "use_cache": false, | |
| "vocab_size": 50304, | |
| "auto_map": { | |
| "AutoConfig": "modeling_tridlm.TriDLMConfig", | |
| "AutoModel": "modeling_tridlm.TriDLMForMaskedDiffusion" | |
| } | |
| } |