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Model: Writer/palmyra-mini-thinking-a Source: Original Platform
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README.md
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README.md
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---
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tags:
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- Coder
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- Math
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- qwen2
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- thinking
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- reasoning
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model-index:
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- name: Palmyra-mini-thinking-a
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results: []
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license: apache-2.0
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pipeline_tag: text-generation
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language:
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- en
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library_name: transformers
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---
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<div align="center">
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<h1>Palmyra-mini-thinking-a</h1>
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</div>
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### Model Description
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- **Language(s) (NLP):** English
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- **License:** Apache-2.0
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- **Finetuned from model:** Qwen/Qwen2.5-1.5B
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- **Context window:** 131,072 tokens
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- **Parameters:** 1.7 billion
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## Model Details
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The palmyra-mini-thinking-a model demonstrates exceptional performance in advanced mathematical reasoning and competitive programming. Its capabilities are highlighted by an outstanding score of 0.886 on the 'MATH500' benchmark, showcasing a robust ability to solve complex mathematical problems. The strength of the model in quantitative challenges is further confirmed by its score of 0.8287 on 'gsm8k (strict-match)', which demonstrates proficiency in multi-step arithmetic reasoning. Additionally, the model proves its aptitude for high-level problem-solving with a score of 0.8 on 'AMC23'. The model also shows strong potential in the coding domain, achieving a score of 0.5631 on 'Codeforces (pass_rate)' and 0.5481 on 'Olympiadbench (extractive_match)', indicating competence in generating correct solutions for programming challenges.
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## Benchmark Performance
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This section provides a detailed breakdown of the palmyra-mini-thinking-a model's performance across a standardized set of industry benchmarks. The data is presented in its original order from the source evaluation.
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| Benchmark | Score |
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|:-----------------------------------------------------------------|---------:|
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| gsm8k (strict-match) | 0.8287 |
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| minerva_math(exact_match) | 0.3842 |
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| mmlu_pro(exact_match) | 0.2748 |
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| hendrycks_math | 0.0054 |
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| ifeval (inst_level_loose_acc) | 0.3657 |
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| mathqa (acc) | 0.4171 |
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| humaneval (pass@1) | 0.2378 |
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| BBH (get-answer)(exact_match) | 0.462 |
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| mbpp | 0.304 |
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| leadboard_musr (acc_norm) | 0.3413 |
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| gpqa lighteval gpqa diamond_pass@1:8_samples | 0.3826 |
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| AIME24(pass@1)(avg-of-1) | 0.4333 |
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| AIME25(pass@1)(avg-of-1) | 0.3667 |
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| Livecodebench-codegen (livecodebench/code_generation_lite v4_v5) | 0.1784 |
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| AMC23 | 0.8 |
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| MATH500 | 0.886 |
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| Minerva | 0.3493 |
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| Olympiadbench (extractive_match) | 0.5481 |
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| Codecontests (pass_rate) | 0.1778 |
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| Codeforces (pass_rate) | 0.5631 |
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| Taco (pass_rate) | 0.3083 |
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| APPS (all_levels) | 0.0447 |
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| HMMT23 (extractive_match) | 0.1 |
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| Average | 0.380839 |
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### Use with transformers
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You can run conversational inference using the Transformers Auto classes with the `generate()` function. Here's an example:
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```py
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "Writer/palmyra-mini-thinking-a"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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attn_implementation="flash_attention_2",
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)
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messages = [
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{
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"role": "user",
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"content": "You have a 3-liter jug and a 5-liter jug. How can you measure exactly 4 liters of water?"
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}
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],
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input_ids = tokenizer.apply_chat_template(
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messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
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)
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gen_conf = {
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"max_new_tokens": 256,
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"eos_token_id": tokenizer.eos_token_id,
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"temperature": 0.3,
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"top_p": 0.9,
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}
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with torch.inference_mode():
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output_id = model.generate(input_ids, **gen_conf)
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output_text = tokenizer.decode(output_id[0][input_ids.shape[1] :])
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print(output_text)
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```
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## Running with vLLM
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```py
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vllm serve Writer/palmyra-mini-thinking-a
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```
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```py
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curl -X POST http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "Writer/palmyra-mini-thinking-a",
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"messages": [
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{
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"role": "user",
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"content": "You have a 3-liter jug and a 5-liter jug. How can you measure exactly 4 liters of water?"
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}
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],
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"max_tokens": 8000,
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"temperature": 0.2
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}'
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```
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## Ethical Considerations
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As with any language model, there is a potential for generating biased or inaccurate information. Users should be aware of these limitations and use the model responsibly.
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### Citation and Related Information
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To cite this model:
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```
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@misc{Palmyra-mini-thinking-a,
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author = {Writer Engineering team},
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title = {{Palmyra-mini: A powerful LLM designed for math and coding}},
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howpublished = {\url{https://dev.writer.com}},
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year = 2025,
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month = Sep
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}
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```
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Contact Hello@writer.com
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chat_template.jinja
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{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\\n'}}{% endif %}
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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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"Qwen2ForCausalLM"
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"layer_types": [
|
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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}
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|
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|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"bos_token": "<|begin▁of▁sentence|>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|end▁of▁sentence|>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"max_length": null,
|
||||
"model_max_length": 16384,
|
||||
"pad_to_multiple_of": null,
|
||||
"pad_token": "<|end▁of▁sentence|>",
|
||||
"pad_token_type_id": 0,
|
||||
"padding_side": "left",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizerFast",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user