Qwen/Qwen2.5-14B-Instruct-AWQ
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Co-authored-by: Vaibhav Srivastav <reach-vb@users.noreply.huggingface.co>
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ai-modelscope
2025-02-27 01:08:53 +08:00
parent 8db7ae15c6
commit 22a88a22d3
1 changed files with 6 additions and 6 deletions
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README.md
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@@ -1,10 +1,11 @@
--- ---
license: apache-2.0 base_model: Qwen/Qwen2.5-14B-Instruct
license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ/blob/main/LICENSE
language: language:
- en - en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ/blob/main/LICENSE
pipeline_tag: text-generation pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-14B-Instruct
tags: tags:
- chat - chat
--- ---
@@ -49,8 +50,8 @@ 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 modelscope import AutoModelForCausalLM, AutoTokenizer from transformers 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",
@@ -76,7 +77,6 @@ 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