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
| { | |
| "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" | |
| } | |