dododododo
commited on
Commit
•
15e2355
1
Parent(s):
7b41de4
Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
|
3 |
+
# Doc / guide: https://huggingface.co/docs/hub/model-cards
|
4 |
+
{}
|
5 |
+
---
|
6 |
+
|
7 |
+
# CT-LLM-Base
|
8 |
+
[**🌐 Homepage**](https://chinese-tiny-llm.github.io) | [**🤗 MAP-CC**](https://huggingface.co/datasets/m-a-p/MAP-CC) | [**🤗 CHC-Bench**](https://huggingface.co/datasets/m-a-p/CHC-Bench) | [**🤗 CT-LLM**](https://huggingface.co/collections/m-a-p/chinese-tiny-llm-660d0133dff6856f94ce0fc6) | [**📖 arXiv**]() | [**GitHub**](https://github.com/Chinese-Tiny-LLM/Chinese-Tiny-LLM)
|
9 |
+
|
10 |
+
CT-LLM-Base is the first Chinese-centric large language model, both pre-training and fine-tuned primarily on Chinese corpora, and offers significant insights into potential biases, Chinese language ability, and multilingual adaptability.
|
11 |
+
|
12 |
+
## Uses
|
13 |
+
|
14 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
15 |
+
```
|
16 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
17 |
+
|
18 |
+
model_path = '<your-model-path>'
|
19 |
+
|
20 |
+
tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False, trust_remote_code=True)
|
21 |
+
|
22 |
+
model = AutoModelForCausalLM.from_pretrained(
|
23 |
+
model_path,
|
24 |
+
device_map="auto",
|
25 |
+
torch_dtype='auto'
|
26 |
+
).eval()
|
27 |
+
|
28 |
+
input_text = "很久很久以前,"
|
29 |
+
|
30 |
+
input_ids = tokenizer(input_text, add_generation_prompt=True, return_tensors='pt').to(model.device)
|
31 |
+
output_ids = model.generate(**input_ids, max_new_tokens=20)
|
32 |
+
response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
|
33 |
+
|
34 |
+
print(response)
|
35 |
+
|
36 |
+
```
|