Qwen/Qwen2.5-14B-Instruct-AWQ
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huangjintao
2024-09-18 15:54:32 +00:00
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@@ -49,8 +49,8 @@ Also check out our [AWQ documentation](https://qwen.readthedocs.io/en/latest/qua
Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents. Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
```python ```python
from transformers import AutoModelForCausalLM, AutoTokenizer from modelscope import AutoModelForCausalLM, AutoTokenizer
model_name = "Qwen/Qwen2.5-14B-Instruct-AWQ" model_name = "qwen/Qwen2.5-14B-Instruct-AWQ"
model = AutoModelForCausalLM.from_pretrained( model = AutoModelForCausalLM.from_pretrained(
model_name, model_name,
torch_dtype="auto", torch_dtype="auto",
@@ -76,6 +76,7 @@ generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
] ]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
``` ```
### Processing Long Texts ### Processing Long Texts