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Model: yufeng1/Apriel-15B-type6-e5-max-1e4-alpha0_75-2 Source: Original Platform
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README.md
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---
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library_name: transformers
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tags: []
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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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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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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|
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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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|
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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|
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[More Information Needed]
|
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|
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#### Metrics
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|
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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|
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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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|
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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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|
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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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34
chat_template.jinja
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chat_template.jinja
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{%- set available_tool_string, add_tool_id = '', true -%}{%- set reasoning_prompt='You are a thoughtful and systematic AI assistant built by ServiceNow Language Models (SLAM) lab. Before providing an answer, analyze the problem carefully and present your reasoning step by step. After explaining your thought process, provide the final solution in the following format: [BEGIN FINAL RESPONSE] ... [END FINAL RESPONSE].' -%}{%- set reasoning_asst_turn_start='Here are my reasoning steps:
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' -%}{%- if tools is not none and tools|length > 0 -%} {%- set available_tools_string -%}You are provided with function signatures within <available_tools></available_tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about the arguments. You should infer the argument values from previous user responses and the system message. Here are the available tools: <available_tools>{% for tool in tools %}{{ tool|string }}{% endfor %}</available_tools>.
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Return all function calls as a list of json objects within <tool_calls></tool_calls> XML tags. Each json object should contain a function name and arguments as follows: <tool_calls>[{"name": <function-name-1>, "arguments": <args-dict-1>}, {"name": <function-name-2>, "arguments": <args-dict-2>},...]</tool_calls> {%- endset -%}{%- endif -%}{%- if messages[0]['role'] != 'system' -%}{%- if tools is not none and tools|length > 0 -%} {{- '<|system|>
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' + reasoning_prompt + '
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' + available_tools_string + '
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<|end|>
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' -}} {%- else -%} {{- '<|system|>
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' + reasoning_prompt + '
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<|end|>
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' -}} {%- endif -%}{%- endif -%}{%- for message in messages -%} {%- if message['role'] == 'user' -%} {{- '<|user|>
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' + message['content'] + '
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<|end|>
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' -}} {%- elif message['role'] == 'system' -%} {%- if tools is not none and tools|length > 0 -%} {{- '<|system|>
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' + reasoning_prompt + '
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' + message['content'] + '
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' + available_tools_string + '
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<|end|>
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' -}} {%- else -%} {{- '<|system|>
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' + reasoning_prompt + '
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' + message['content'] + '
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<|end|>
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' -}} {%- endif -%} {%- elif message['role'] == 'assistant' -%} {%- if loop.last -%} {%- set add_tool_id = false -%} {%- endif -%} {{- '<|assistant|>
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' -}} {%- if message['content'] is not none -%} {{- message['content'] -}} {%- elif message['chosen'] is not none and message['chosen']|length > 0 -%} {{- message['chosen'][0] -}} {%- endif -%} {%- if message['tool_calls'] is not none and message['tool_calls']|length > 0 -%} {{- '
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<tool_calls>[' -}} {%- for tool_call in message["tool_calls"] -%} {{- '{"name": "' + tool_call['function']['name'] + '", "arguments": ' + tool_call['function']['arguments']|string -}} {%- if add_tool_id == true -%} {{- ', "id": "' + tool_call['id'] -}} {%- endif -%} {{- '}' -}} {%- if not loop.last -%}{{- ', ' -}}{%- endif -%} {%- endfor -%} {{- ']</tool_calls>' -}} {%- endif -%} {%- if not loop.last or training_prompt -%} {{- '
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<|end|>
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' -}} {%- endif -%} {%- elif message['role'] == 'tool' -%} {{- '<|tool_result|>
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' + message['content']|string + '
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<|end|>
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' -}} {%- endif -%} {%- if loop.last and add_generation_prompt and message['role'] != 'assistant' -%} {{- '<|assistant|>
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' + reasoning_asst_turn_start -}} {%- endif -%}{%- endfor -%}
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config.json
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config.json
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{
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"dtype": "bfloat16",
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 65536,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 50,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.1",
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"use_cache": true,
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"vocab_size": 131072
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}
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generation_config.json
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.57.1"
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}
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||||
}
|
||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
|
||||
size 17078292
|
||||
8015
tokenizer_config.json
Normal file
8015
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user