Feature Extraction
Transformers
TensorBoard
Safetensors
opensci
llama-factory
full
Generated from Trainer
custom_code
Instructions to use open-sci/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use open-sci/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="open-sci/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("open-sci/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0 / chat_template.jinja
| {%- for message in messages -%} | |
| {%- if message["role"] == "system" -%} | |
| {{- "<|system|> | |
| " + message["content"] + " | |
| " -}} | |
| {%- elif message["role"] == "user" -%} | |
| {{- "<|user|> | |
| " + message["content"] + " | |
| " -}} | |
| {%- elif message["role"] == "assistant" -%} | |
| {%- if not loop.last -%} | |
| {{- "<|assistant|> | |
| " + message["content"] + eos_token + " | |
| " -}} | |
| {%- else -%} | |
| {{- "<|assistant|> | |
| " + message["content"] + eos_token -}} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- if loop.last and add_generation_prompt -%} | |
| {{- "<|assistant|> | |
| " -}} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt %} | |
| {{- '<|im_start|>assistant\n' }} | |
| {%- if enable_thinking is defined and enable_thinking is false %} | |
| {{- '<think>\n\n</think>\n\n' }} | |
| {%- endif %} | |
| {%- endif %} |