Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
datasets:
|
| 4 |
+
- allenai/tulu-3-sft-mixture
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
base_model:
|
| 8 |
+
- hamishivi/tess2-v0.3-base
|
| 9 |
+
---
|
| 10 |
+
# TESS 2 v0.3 - A Generalist Instruction Tuned Diffusion LM
|
| 11 |
+
|
| 12 |
+
This model is the instruction-tuned TESS 2. This model is a simplex-based diffusion model adapted from Mistral v0.1 7B, further trained on Dolma 1.7 and Tulu 3 SFT data.
|
| 13 |
+
For more details, please check out our paper [TESS-2: A Large-Scale, Generalist Diffusion Language Model](https://todo).
|
| 14 |
+
This is the model based on Mistral v0.3 and Tulu 3.
|
| 15 |
+
|
| 16 |
+
This model will only work with our custom codebase found [here](https://github.com/hamishivi/tess-2) -- please go there to see details on how to run training and inference.
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Using this model
|
| 20 |
+
|
| 21 |
+
To run this model, first clone https://github.com/hamishivi/tess-2.
|
| 22 |
+
|
| 23 |
+
Then, after creating a python environment with the correct packages, you can run inference via a ui with:
|
| 24 |
+
```sh
|
| 25 |
+
./shell_scripts/run_interactive_demo.sh hamishivi/tess2
|
| 26 |
+
```
|
| 27 |
+
|
| 28 |
+
This allows you to directly interact with the model, and shows the diffusion generation process.
|
| 29 |
+
For training or other evaluations, please see our main repository.
|