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: 575 Bytes
6611f0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"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"
}
} |