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linglingdan
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Model Details
Model Provider
linglingdan
Model Tree
Base
Qwen/Qwen3-8B
Fine-tuned
this model
Input Modalities
Text
Output Modalities
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Supported Functionality
Dedicated Endpoints
Container
Qwen/Qwen3-8BQwen3ForCausalLMbfloat16max_position_embeddings = 40960safetensors (4 shards)python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizermodel_name = "Yiwei6534/Qwen3-8B-Physics"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(model_name,torch_dtype=torch.bfloat16,device_map="auto",trust_remote_code=True,)messages = [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "What can you help me with?"},]text = tokenizer.apply_chat_template(messages,tokenize=False,add_generation_prompt=True,)inputs = tokenizer(text, return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=256)print(tokenizer.decode(outputs[0], skip_special_tokens=True))
The bundled generation_config.json uses temperature=0.6, top_k=20, top_p=0.95. Adjust based on your deployment.
FILE_MANIFEST.json: list of distributed files and their byte sizes.SHA256SUMS.txt: SHA256 checksums for all distributed files (verify with sha256sum -c SHA256SUMS.txt).This repository uses license: other as a placeholder. Replace it with the correct license for the base model, your fine-tuning data, and your distribution terms before publishing.