Instructions to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MT5ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
Update tiny models for MT5ForSequenceClassification
#29
by hf-transformers-bot - opened
- config.json +1 -1
- model.safetensors +1 -1
- tokenizer_config.json +1 -0
config.json
CHANGED
|
@@ -26,7 +26,7 @@
|
|
| 26 |
"tie_word_embeddings": false,
|
| 27 |
"tokenizer_class": "T5Tokenizer",
|
| 28 |
"torch_dtype": "float32",
|
| 29 |
-
"transformers_version": "4.
|
| 30 |
"use_cache": true,
|
| 31 |
"vocab_size": 250100
|
| 32 |
}
|
|
|
|
| 26 |
"tie_word_embeddings": false,
|
| 27 |
"tokenizer_class": "T5Tokenizer",
|
| 28 |
"torch_dtype": "float32",
|
| 29 |
+
"transformers_version": "4.39.0.dev0",
|
| 30 |
"use_cache": true,
|
| 31 |
"vocab_size": 250100
|
| 32 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 32180840
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c67d3a4aa402fc12e727585d505809d0b08629cf1b79188fc269fdb60cdee089
|
| 3 |
size 32180840
|
tokenizer_config.json
CHANGED
|
@@ -1,4 +1,5 @@
|
|
| 1 |
{
|
|
|
|
| 2 |
"added_tokens_decoder": {
|
| 3 |
"0": {
|
| 4 |
"content": "<pad>",
|
|
|
|
| 1 |
{
|
| 2 |
+
"add_prefix_space": true,
|
| 3 |
"added_tokens_decoder": {
|
| 4 |
"0": {
|
| 5 |
"content": "<pad>",
|