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.gitattributes | ||
LICENSE | ||
README.md | ||
README_en.md | ||
config.json | ||
generation_config.json | ||
model-00001-of-00002.safetensors | ||
model-00002-of-00002.safetensors | ||
model.safetensors.index.json | ||
special_tokens_map.json | ||
tokenizer.json | ||
tokenizer_config.json |
README_en.md
GLM-Edge-1.5B-Chat
中文阅读, 点击这里
Inference with Transformers
Installation
Install the transformers library from the source code:
pip install git+https://github.com/huggingface/transformers.git
Inference
from transformers import AutoModelForCausalLM, AutoTokenizer
MODEL_PATH = "THUDM/glm-edge-4b-chat"
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
message = [{"role": "user", "content": "hello!"}]
inputs = tokenizer.apply_chat_template(
message,
return_tensors="pt",
add_generation_prompt=True,
return_dict=True,
).to(model.device)
generate_kwargs = {
"input_ids": inputs["input_ids"],
"attention_mask": inputs["attention_mask"],
"max_new_tokens": 128,
"do_sample": False,
}
out = model.generate(**generate_kwargs)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
License
The usage of this model’s weights is subject to the terms outlined in the LICENSE.