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loras/better-tool-call/README.md
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loras/better-tool-call/README.md
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---
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base_model: HuggingFaceTB/SmolLM3-3B
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library_name: peft
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:HuggingFaceTB/SmolLM3-3B
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- lora
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- transformers
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.18.1
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46
loras/better-tool-call/adapter_config.json
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loras/better-tool-call/adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "HuggingFaceTB/SmolLM3-3B",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"gate_proj",
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"v_proj",
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"k_proj",
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"o_proj",
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"down_proj",
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"q_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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BIN
loras/better-tool-call/adapter_model.safetensors
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loras/better-tool-call/adapter_model.safetensors
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loras/better-tool-call/chat_template.jinja
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{# ───── defaults ───── #}
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{%- if enable_thinking is not defined -%}
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{%- set enable_thinking = true -%}
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{%- endif -%}
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{# ───── reasoning mode ───── #}
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{%- if enable_thinking -%}
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{%- set reasoning_mode = "/think" -%}
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{%- else -%}
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{%- set reasoning_mode = "/no_think" -%}
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{%- endif -%}
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{# ───── header (system message) ───── #}
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{{- "<|im_start|>system\n" -}}
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{%- if messages[0].role == "system" -%}
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{%- set system_message = messages[0].content -%}
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{%- if "/no_think" in system_message -%}
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{%- set reasoning_mode = "/no_think" -%}
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{%- elif "/think" in system_message -%}
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{%- set reasoning_mode = "/think" -%}
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{%- endif -%}
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{%- set custom_instructions = system_message.replace("/no_think", "").replace("/think", "").rstrip() -%}
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{%- endif -%}
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{%- if "/system_override" in system_message -%}
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{{- custom_instructions.replace("/system_override", "").rstrip() -}}
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{{- "<|im_end|>\n" -}}
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{%- else -%}
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{{- "## Metadata\n\n" -}}
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{{- "Knowledge Cutoff Date: June 2025\n" -}}
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{%- set today = strftime_now("%d %B %Y") -%}
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{{- "Today Date: " ~ today ~ "\n" -}}
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{{- "Reasoning Mode: " + reasoning_mode + "\n\n" -}}
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{{- "## Custom Instructions\n\n" -}}
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{%- if custom_instructions -%}
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{{- custom_instructions + "\n\n" -}}
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{%- elif reasoning_mode == "/think" -%}
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{{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face. Your role as an assistant involves thoroughly exploring questions through a systematic thinking process before providing the final precise and accurate solutions. This requires engaging in a comprehensive cycle of analysis, summarizing, exploration, reassessment, reflection, backtracking, and iteration to develop well-considered thinking process. Please structure your response into two main sections: Thought and Solution using the specified format: <think> Thought section </think> Solution section. In the Thought section, detail your reasoning process in steps. Each step should include detailed considerations such as analysing questions, summarizing relevant findings, brainstorming new ideas, verifying the accuracy of the current steps, refining any errors, and revisiting previous steps. In the Solution section, based on various attempts, explorations, and reflections from the Thought section, systematically present the final solution that you deem correct. The Solution section should be logical, accurate, and concise and detail necessary steps needed to reach the conclusion.\n\n" -}}
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{%- else -%}
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{{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face.\n\n" -}}
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{%- endif -%}
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{%- if xml_tools or python_tools or tools -%}
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{{- "### Tools\n\n" -}}
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{%- if xml_tools or tools -%}
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{%- if tools -%}
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{%- set xml_tools = tools -%}
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{%- endif -%}
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{%- set ns = namespace(xml_tool_string="You may call one or more functions to assist with the user query.\nYou are provided with function signatures within <tools></tools> XML tags:\n\n<tools>\n") -%}
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{%- for tool in xml_tools[:] -%} {# The slicing makes sure that xml_tools is a list #}
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{%- set ns.xml_tool_string = ns.xml_tool_string ~ (tool | string) ~ "\n" -%}
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{%- endfor -%}
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{%- set xml_tool_string = ns.xml_tool_string + "</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call>" -%}
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{{- xml_tool_string -}}
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{%- endif -%}
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{%- if python_tools -%}
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{%- set ns = namespace(python_tool_string="When you send a message containing Python code between '<code>' and '</code>' tags, it will be executed in a stateful Jupyter notebook environment, and you will then be given the output to continued reasoning in an agentic loop.\n\nYou can use the following tools in your python code like regular functions:\n<tools>\n") -%}
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{%- for tool in python_tools[:] -%} {# The slicing makes sure that python_tools is a list #}
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{%- set ns.python_tool_string = ns.python_tool_string ~ (tool | string) ~ "\n" -%}
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{%- endfor -%}
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{%- set python_tool_string = ns.python_tool_string + "</tools>\n\nThe state persists between code executions: so variables that you define in one step are still available thereafter." -%}
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{{- python_tool_string -}}
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{%- endif -%}
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{{- "\n\n" -}}
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{{- "<|im_end|>\n" -}}
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{%- endif -%}
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{%- endif -%}
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{# ───── main loop ───── #}
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{%- for message in messages -%}
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{%- set content = message.content if message.content is string else "" -%}
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{%- if message.role == "user" -%}
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{{ "<|im_start|>" + message.role + "\n" + content + "<|im_end|>\n" }}
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{%- elif message.role == "assistant" -%}
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{% generation %}
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{%- if reasoning_mode == "/think" -%}
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{{ "<|im_start|>assistant\n" + content.lstrip("\n") + "<|im_end|>\n" }}
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{%- else -%}
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{{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" + content.lstrip("\n") + "<|im_end|>\n" }}
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{%- endif -%}
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{% endgeneration %}
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{%- elif message.role == "tool" -%}
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{{ "<|im_start|>" + "user\n" + content + "<|im_end|>\n" }}
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{%- endif -%}
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{%- endfor -%}
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{# ───── generation prompt ───── #}
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{%- if add_generation_prompt -%}
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{%- if reasoning_mode == "/think" -%}
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{{ "<|im_start|>assistant\n" }}
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{%- else -%}
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{{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" }}
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{%- endif -%}
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{%- endif -%}
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1250970
loras/better-tool-call/tokenizer.json
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loras/better-tool-call/tokenizer.json
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loras/better-tool-call/tokenizer_config.json
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loras/better-tool-call/tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": null,
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|im_end|>",
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"fast": false,
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"is_local": false,
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 131072,
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"pad_token": "<|im_end|>",
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"tokenizer_class": "TokenizersBackend"
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}
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Reference in New Issue
Block a user