Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
datasets:
|
3 |
+
- heegyu/wizard_vicuna_70k_v2
|
4 |
+
---
|
5 |
+
|
6 |
+
Hyperparameters
|
7 |
+
- 3 epoch
|
8 |
+
- 1e-4 -> 1e-5 with cosine lr decay
|
9 |
+
- batch size 128
|
10 |
+
- max sequence length 2048
|
11 |
+
- AdamW(weigth decay=0.01, b1=0.9, b2=0.99, grad_clip=1.0)
|
12 |
+
- no warmup
|
13 |
+
- BF16
|
14 |
+
|
15 |
+
```
|
16 |
+
# Load model directly
|
17 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
18 |
+
|
19 |
+
tokenizer = AutoTokenizer.from_pretrained("heegyu/WizardVicuna-pythia-1.4b-deduped")
|
20 |
+
model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-pythia-1.4b-deduped")
|
21 |
+
|
22 |
+
inputs = tokenizer(["Human: Hi\n\nAssistant: "], return_tensors="pt")
|
23 |
+
outputs = model.generate(**inputs, max_new_tokens=16)
|
24 |
+
print(tokenizer.batch_decode(outputs, skip_special_tokens=False))
|
25 |
+
```
|
26 |
+
|
27 |
+
output: `['Human: Hi\n\nAssistant: Hello! How can I assist you today?<|endoftext|>']`
|