Instructions to use rendchevi/text-to-code-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rendchevi/text-to-code-v0.1 with Transformers:
# Load model directly from transformers import SpeakerConditionedCausalLM model = SpeakerConditionedCausalLM.from_pretrained("rendchevi/text-to-code-v0.1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 915437728
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:53bc0b9ef5d5db184df204a3e4e6c71ecc6cf875a5eced52a23b552fb5a47a35
|
| 3 |
size 915437728
|