Instructions to use MattLips/Llama1B_Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattLips/Llama1B_Instruct with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MattLips/Llama1B_Instruct", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use MattLips/Llama1B_Instruct 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 MattLips/Llama1B_Instruct 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 MattLips/Llama1B_Instruct to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MattLips/Llama1B_Instruct to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="MattLips/Llama1B_Instruct", max_seq_length=2048, )
Delete special_tokens_map.json
Browse files- special_tokens_map.json +0 -23
special_tokens_map.json
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{
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"bos_token": {
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"content": "<|begin_of_text|>",
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"lstrip": false,
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"eos_token": {
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"content": "<|end_of_text|>",
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"normalized": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|finetune_right_pad_id|>",
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"lstrip": false,
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"normalized": false,
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