Feature Extraction
Transformers
Safetensors
English
smb_unstructured
text-generation
World Model
Patient Representation Encoder
Feature Extraction
Joint Embedding Predictive Architecture (JEPA)
custom_code
Instructions to use anon-9421/smb-structure-llama3-8b-multi-objective with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anon-9421/smb-structure-llama3-8b-multi-objective with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="anon-9421/smb-structure-llama3-8b-multi-objective", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("anon-9421/smb-structure-llama3-8b-multi-objective", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "smb_unstructured", | |
| "architectures": [ | |
| "SMBUnstructuredForCausalLM" | |
| ], | |
| "llm_model_name_or_path": "./Meta-Llama-3-8B", | |
| "tokenizer_name_or_path": "./Meta-Llama-3-8B", | |
| "hidden_size": 4096, | |
| "vocab_size": 128272, | |
| "pad_token": "<|end_of_text|>", | |
| "pad_token_id": 128001, | |
| "tokenizer_padding_side": "right", | |
| "tokenizer_model_max_length": 3300, | |
| "use_cache": true, | |
| "auto_map": { | |
| "AutoConfig": "modeling_smb_unstructured.SMBUnstructuredConfig", | |
| "AutoModelForCausalLM": "modeling_smb_unstructured.SMBUnstructuredForCausalLM" | |
| }, | |
| "text_config": { | |
| "_name_or_path": "./Meta-Llama-3-8B", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 500000.0, | |
| "torch_dtype": "bfloat16", | |
| "use_cache": true, | |
| "vocab_size": 128272 | |
| } | |
| } |