Instructions to use IngeniousArtist/openllama-3b-finance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IngeniousArtist/openllama-3b-finance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IngeniousArtist/openllama-3b-finance")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IngeniousArtist/openllama-3b-finance") model = AutoModelForSequenceClassification.from_pretrained("IngeniousArtist/openllama-3b-finance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "openlm-research/open_llama_3b_v2", | |
| "architectures": [ | |
| "LlamaForSequenceClassification" | |
| ], | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 3200, | |
| "id2label": { | |
| "0": "Negative", | |
| "1": "Neutral", | |
| "2": "Positive" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8640, | |
| "label2id": { | |
| "Negative": 0, | |
| "Neutral": 1, | |
| "Positive": 2 | |
| }, | |
| "max_position_embeddings": 2048, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 26, | |
| "num_key_value_heads": 32, | |
| "pad_token_id": 2, | |
| "pretraining_tp": 1, | |
| "problem_type": "single_label_classification", | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.32.0", | |
| "use_cache": false, | |
| "vocab_size": 32000 | |
| } | |