Spaces:
Running
on
Zero
Running
on
Zero
Update
Browse files
README.md
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
---
|
| 2 |
-
title: Zephyr 7b
|
| 3 |
emoji: ๐
|
| 4 |
colorFrom: green
|
| 5 |
colorTo: yellow
|
|
@@ -11,4 +11,6 @@ license: mit
|
|
| 11 |
suggested-hardware: t4-small
|
| 12 |
---
|
| 13 |
|
|
|
|
|
|
|
| 14 |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
|
|
|
| 1 |
---
|
| 2 |
+
title: Zephyr 7b
|
| 3 |
emoji: ๐
|
| 4 |
colorFrom: green
|
| 5 |
colorTo: yellow
|
|
|
|
| 11 |
suggested-hardware: t4-small
|
| 12 |
---
|
| 13 |
|
| 14 |
+
https://arxiv.org/abs/2310.16944
|
| 15 |
+
|
| 16 |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
app.py
CHANGED
|
@@ -9,7 +9,7 @@ import spaces
|
|
| 9 |
import torch
|
| 10 |
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
|
| 11 |
|
| 12 |
-
DESCRIPTION = "# Zephyr-7B
|
| 13 |
|
| 14 |
if not torch.cuda.is_available():
|
| 15 |
DESCRIPTION += "\n<p>Running on CPU ๐ฅถ This demo does not work on CPU.</p>"
|
|
@@ -19,7 +19,7 @@ DEFAULT_MAX_NEW_TOKENS = 1024
|
|
| 19 |
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
|
| 20 |
|
| 21 |
if torch.cuda.is_available():
|
| 22 |
-
model_id = "HuggingFaceH4/zephyr-7b-
|
| 23 |
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
|
| 24 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
| 25 |
|
|
|
|
| 9 |
import torch
|
| 10 |
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
|
| 11 |
|
| 12 |
+
DESCRIPTION = "# Zephyr-7B beta"
|
| 13 |
|
| 14 |
if not torch.cuda.is_available():
|
| 15 |
DESCRIPTION += "\n<p>Running on CPU ๐ฅถ This demo does not work on CPU.</p>"
|
|
|
|
| 19 |
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
|
| 20 |
|
| 21 |
if torch.cuda.is_available():
|
| 22 |
+
model_id = "HuggingFaceH4/zephyr-7b-beta"
|
| 23 |
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
|
| 24 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
| 25 |
|