update tool call
#12
by Navanit-AI - opened
- README.md +4 -4
- SYSTEM_PROMPT.txt +2 -1
- params.json +1 -2
- tokenizer_config.json +1 -1
README.md
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@@ -1,5 +1,4 @@
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---
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library_name: vllm
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language:
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- en
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- fr
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@@ -12,6 +11,7 @@ language:
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- ru
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- ko
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license: apache-2.0
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inference: false
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base_model:
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- mistralai/Mistral-Small-24B-Base-2501
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If you want to learn more about how we process your personal data, please read
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our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
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tags:
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-
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---
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# Model Card for Mistral-Small-24B-Instruct-2501
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## Usage
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The model can be used with the following frameworks;
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- [`vllm`](https://github.com/vllm-project/vllm): See [here](#
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- [`transformers`](https://github.com/huggingface/transformers): See [here](#
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### vLLM
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---
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language:
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- en
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- fr
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- ru
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- ko
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license: apache-2.0
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library_name: vllm
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inference: false
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base_model:
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- mistralai/Mistral-Small-24B-Base-2501
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If you want to learn more about how we process your personal data, please read
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our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
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tags:
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- transformers
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---
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# Model Card for Mistral-Small-24B-Instruct-2501
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## Usage
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The model can be used with the following frameworks;
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- [`vllm`](https://github.com/vllm-project/vllm): See [here](#vLLM)
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- [`transformers`](https://github.com/huggingface/transformers): See [here](#Transformers)
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### vLLM
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SYSTEM_PROMPT.txt
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@@ -6,4 +6,5 @@ The current date is {today}.
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When you're not sure about some information, you say that you don't have the information and don't make up anything.
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If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. "What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "Where do you travel from?").
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You are always very attentive to dates, in particular you try to resolve dates (e.g. "yesterday" is {yesterday}) and when asked about information at specific dates, you discard information that is at another date.
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You follow these instructions in all languages, and always respond to the user in the language they use or request.
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When you're not sure about some information, you say that you don't have the information and don't make up anything.
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If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. "What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "Where do you travel from?").
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You are always very attentive to dates, in particular you try to resolve dates (e.g. "yesterday" is {yesterday}) and when asked about information at specific dates, you discard information that is at another date.
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You follow these instructions in all languages, and always respond to the user in the language they use or request.
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Next sections describe the capabilities that you have.
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params.json
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"norm_eps": 1e-05,
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"vocab_size": 131072,
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"rope_theta": 100000000.0,
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"max_seq_len": 32768
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"max_position_embeddings": 32768
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}
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"norm_eps": 1e-05,
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"vocab_size": 131072,
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"rope_theta": 100000000.0,
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"max_seq_len": 32768
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}
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tokenizer_config.json
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"eos_token": "</s>",
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"extra_special_tokens": {},
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"legacy": true,
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"model_max_length":
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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"eos_token": "</s>",
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"extra_special_tokens": {},
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"legacy": true,
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"model_max_length": 1000000000000000019884624838656,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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