Feature Extraction
Transformers
Safetensors
qwen
llama-factory
freeze
Generated from Trainer
custom_code
Instructions to use mohit95559/mymodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohit95559/mymodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mohit95559/mymodel", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mohit95559/mymodel", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 745 Bytes
10631da | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"added_tokens_decoder": {},
"auto_map": {
"AutoTokenizer": [
"tokenization_qwen.QWenTokenizer",
null
]
},
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ content }}{% elif message['role'] == 'assistant' %}{{ content }}{% endif %}{% endfor %}",
"clean_up_tokenization_spaces": true,
"eos_token": "<|endoftext|>",
"model_max_length": 32768,
"pad_token": "<|endoftext|>",
"padding_side": "right",
"split_special_tokens": false,
"tokenizer_class": "QWenTokenizer"
}
|