Instructions to use mgh6/esm_temp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/esm_temp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/esm_temp2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/esm_temp2") model = AutoModelForMaskedLM.from_pretrained("mgh6/esm_temp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 136048297
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e1554298b82f3bc4b5906c96d6633d58fb7e435619e3c7bca4b2aab79ecc3078
|
| 3 |
size 136048297
|
runs/Aug04_19-50-50_973859407ab3/events.out.tfevents.1691186752.973859407ab3.1419.31
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9cafbca6fa6d2de8d2ed635c61bc7299e6fdfc2b935f6b65dc5d1621c2890bc4
|
| 3 |
+
size 5091
|
runs/Aug04_19-50-50_973859407ab3/events.out.tfevents.1691187488.973859407ab3.1419.32
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:579f23efdb1ee563754465634b7cbd4b82c62252ea8a56556a9fa18918daf2da
|
| 3 |
+
size 4309
|