Question Answering
Transformers
Safetensors
English
Russian
qwen2
text-generation
qwen
chat
fine-tuned
experimental
trl
sft
text-generation-inference
8-bit precision
Instructions to use markaked/venus-ape with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markaked/venus-ape with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="markaked/venus-ape")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("markaked/venus-ape") model = AutoModelForCausalLM.from_pretrained("markaked/venus-ape") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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],
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"is_local": false,
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"model_max_length": 131072,
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"pad_token": "<|
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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],
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"is_local": false,
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"model_max_length": 131072,
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"pad_token": "<|im_end|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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