Push model using huggingface_hub.
Browse files
README.md
CHANGED
|
@@ -25,7 +25,7 @@ You can then generate text as follows:
|
|
| 25 |
```python
|
| 26 |
from transformers import pipeline
|
| 27 |
|
| 28 |
-
generator = pipeline("text-generation", model="jvelja//tmp/
|
| 29 |
outputs = generator("Hello, my llama is cute")
|
| 30 |
```
|
| 31 |
|
|
@@ -35,8 +35,8 @@ If you want to use the model for training or to obtain the outputs from the valu
|
|
| 35 |
from transformers import AutoTokenizer
|
| 36 |
from trl import AutoModelForCausalLMWithValueHead
|
| 37 |
|
| 38 |
-
tokenizer = AutoTokenizer.from_pretrained("jvelja//tmp/
|
| 39 |
-
model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/
|
| 40 |
|
| 41 |
inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
|
| 42 |
outputs = model(**inputs, labels=inputs["input_ids"])
|
|
|
|
| 25 |
```python
|
| 26 |
from transformers import pipeline
|
| 27 |
|
| 28 |
+
generator = pipeline("text-generation", model="jvelja//tmp/tmpz_p4ucv5/jvelja/gpt2_imdb_0")
|
| 29 |
outputs = generator("Hello, my llama is cute")
|
| 30 |
```
|
| 31 |
|
|
|
|
| 35 |
from transformers import AutoTokenizer
|
| 36 |
from trl import AutoModelForCausalLMWithValueHead
|
| 37 |
|
| 38 |
+
tokenizer = AutoTokenizer.from_pretrained("jvelja//tmp/tmpz_p4ucv5/jvelja/gpt2_imdb_0")
|
| 39 |
+
model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpz_p4ucv5/jvelja/gpt2_imdb_0")
|
| 40 |
|
| 41 |
inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
|
| 42 |
outputs = model(**inputs, labels=inputs["input_ids"])
|