Instructions to use ModularityAI/gemma-2b-datascience-it-adapters-raft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModularityAI/gemma-2b-datascience-it-adapters-raft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ModularityAI/gemma-2b-datascience-it-adapters-raft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use ModularityAI/gemma-2b-datascience-it-adapters-raft with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ModularityAI/gemma-2b-datascience-it-adapters-raft to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ModularityAI/gemma-2b-datascience-it-adapters-raft to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ModularityAI/gemma-2b-datascience-it-adapters-raft to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ModularityAI/gemma-2b-datascience-it-adapters-raft", max_seq_length=2048, )
File size: 2,162 Bytes
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"add_eos_token": false,
"added_tokens_decoder": {
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"3": {
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"106": {
"content": "<start_of_turn>",
"lstrip": false,
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"single_word": false,
"special": true
},
"107": {
"content": "<end_of_turn>",
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}
},
"additional_special_tokens": [
"<start_of_turn>",
"<end_of_turn>"
],
"bos_token": "<bos>",
"chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
"clean_up_tokenization_spaces": false,
"eos_token": "<eos>",
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"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "GemmaTokenizer",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
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