Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use LinusML/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinusML/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LinusML/my_awesome_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LinusML/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("LinusML/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +56 -0
- model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +15 -0
- training_args.bin +3 -0
config.json
ADDED
|
@@ -0,0 +1,56 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"activation": "gelu",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"DistilBertForSequenceClassification"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.1,
|
| 7 |
+
"bos_token_id": null,
|
| 8 |
+
"dim": 768,
|
| 9 |
+
"dropout": 0.1,
|
| 10 |
+
"dtype": "float32",
|
| 11 |
+
"eos_token_id": null,
|
| 12 |
+
"hidden_dim": 3072,
|
| 13 |
+
"id2label": {
|
| 14 |
+
"0": "A",
|
| 15 |
+
"1": "F",
|
| 16 |
+
"2": "FT",
|
| 17 |
+
"3": "L",
|
| 18 |
+
"4": "LF",
|
| 19 |
+
"5": "MN",
|
| 20 |
+
"6": "O",
|
| 21 |
+
"7": "PE",
|
| 22 |
+
"8": "PO",
|
| 23 |
+
"9": "SC",
|
| 24 |
+
"10": "SE",
|
| 25 |
+
"11": "US"
|
| 26 |
+
},
|
| 27 |
+
"initializer_range": 0.02,
|
| 28 |
+
"label2id": {
|
| 29 |
+
"A": 0,
|
| 30 |
+
"F": 1,
|
| 31 |
+
"FT": 2,
|
| 32 |
+
"L": 3,
|
| 33 |
+
"LF": 4,
|
| 34 |
+
"MN": 5,
|
| 35 |
+
"O": 6,
|
| 36 |
+
"PE": 7,
|
| 37 |
+
"PO": 8,
|
| 38 |
+
"SC": 9,
|
| 39 |
+
"SE": 10,
|
| 40 |
+
"US": 11
|
| 41 |
+
},
|
| 42 |
+
"max_position_embeddings": 512,
|
| 43 |
+
"model_type": "distilbert",
|
| 44 |
+
"n_heads": 12,
|
| 45 |
+
"n_layers": 6,
|
| 46 |
+
"pad_token_id": 0,
|
| 47 |
+
"problem_type": "single_label_classification",
|
| 48 |
+
"qa_dropout": 0.1,
|
| 49 |
+
"seq_classif_dropout": 0.2,
|
| 50 |
+
"sinusoidal_pos_embds": false,
|
| 51 |
+
"tie_weights_": true,
|
| 52 |
+
"tie_word_embeddings": true,
|
| 53 |
+
"transformers_version": "5.18.0",
|
| 54 |
+
"use_cache": false,
|
| 55 |
+
"vocab_size": 30522
|
| 56 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b7556c17988908e59c2d0c2040ceb6f85db4978e412ceab3832ebf1132d535f8
|
| 3 |
+
size 267863328
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"cls_token": "[CLS]",
|
| 4 |
+
"do_lower_case": true,
|
| 5 |
+
"is_local": false,
|
| 6 |
+
"local_files_only": false,
|
| 7 |
+
"mask_token": "[MASK]",
|
| 8 |
+
"model_max_length": 512,
|
| 9 |
+
"pad_token": "[PAD]",
|
| 10 |
+
"sep_token": "[SEP]",
|
| 11 |
+
"strip_accents": null,
|
| 12 |
+
"tokenize_chinese_chars": true,
|
| 13 |
+
"tokenizer_class": "BertTokenizer",
|
| 14 |
+
"unk_token": "[UNK]"
|
| 15 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e4d64b7fb4d902eabad8219db39d93b5d4166df378d06389e940f13a151c285d
|
| 3 |
+
size 5201
|