File size: 1,249 Bytes
54f067d 684ad10 54f067d f3564c8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | ---
library_name: transformers
license: mit
base_model:
- stockmark/Stockmark-2-100B-Instruct-beta
---
# Stockmark-2-100B-Instruct-beta-AWQ
This repo contains the AWQ-quantized 4-bit version of [Stockmark-2-100B-Instruct-beta](https://huggingface.co/stockmark/Stockmark-2-100B-Instruct-beta)
## Example
**Please use the float16 data type when loading the model. The bfloat16 data type is not supported in this model.**
```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("stockmark/Stockmark-2-100B-Instruct-beta-AWQ")
model = AutoModelForCausalLM.from_pretrained("stockmark/Stockmark-2-100B-Instruct-beta-AWQ", device_map="auto", torch_dtype=torch.float16)
instruction = "自然言語処理とは？"
input_ids = tokenizer.apply_chat_template(
[{"role": "user", "content": instruction}], add_generation_prompt=True, return_tensors="pt"
).to(model.device)
with torch.inference_mode():
tokens = model.generate(
input_ids,
max_new_tokens = 512,
do_sample = True,
temperature = 0.7,
top_p = 0.95,
repetition_penalty = 1.05
)
output = tokenizer.decode(tokens[0], skip_special_tokens=True)
print(output)
``` |