Instructions to use Q-bert/try-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Q-bert/try-1b with Transformers:
# Load model directly from transformers import StockLlamaForForecasting model = StockLlamaForForecasting.from_pretrained("Q-bert/try-1b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 727 Bytes
98892eb | 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 27 28 29 30 31 32 | {
"architectures": [
"StockLlamaForForecasting"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 1,
"eos_token_id": 2,
"head_dim": 512,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 4096,
"max_position_embeddings": 2048,
"mlp_bias": false,
"model_type": "stockllama",
"num_attention_heads": 8,
"num_hidden_layers": 8,
"num_key_value_heads": 8,
"pad_token_id": 0,
"pretraining_tp": 1,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 10000.0,
"term_number": 4,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.51.2",
"use_cache": true,
"vocab_size": 10000
}
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