Instructions to use xcczach/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xcczach/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="xcczach/test-model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xcczach/test-model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- configuration_test.py +1 -1
- model.safetensors +1 -1
config.json
CHANGED
|
@@ -7,7 +7,7 @@
|
|
| 7 |
"AutoModel": "modeling_test.TestModel"
|
| 8 |
},
|
| 9 |
"input_dim": 10,
|
| 10 |
-
"model_type": "
|
| 11 |
"output_dim": 5,
|
| 12 |
"torch_dtype": "float32",
|
| 13 |
"transformers_version": "4.39.1"
|
|
|
|
| 7 |
"AutoModel": "modeling_test.TestModel"
|
| 8 |
},
|
| 9 |
"input_dim": 10,
|
| 10 |
+
"model_type": "my_test_model",
|
| 11 |
"output_dim": 5,
|
| 12 |
"torch_dtype": "float32",
|
| 13 |
"transformers_version": "4.39.1"
|
configuration_test.py
CHANGED
|
@@ -3,7 +3,7 @@ from typing import List
|
|
| 3 |
|
| 4 |
|
| 5 |
class TestConfig(PretrainedConfig):
|
| 6 |
-
model_type = "
|
| 7 |
|
| 8 |
def __init__(
|
| 9 |
self,
|
|
|
|
| 3 |
|
| 4 |
|
| 5 |
class TestConfig(PretrainedConfig):
|
| 6 |
+
model_type = "my_test_model"
|
| 7 |
|
| 8 |
def __init__(
|
| 9 |
self,
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 871354852
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:64dd934f5668a34c0a8860dc7e774784c3733afd4bc8231e49be78596cee2b16
|
| 3 |
size 871354852
|