Text Generation
Transformers
Safetensors
English
llama
fireplace
fireplace-2
valiant
valiant-labs
llama-3.1
llama-3.1-instruct
llama-3.1-instruct-8b
llama-3
llama-3-instruct
llama-3-instruct-8b
8b
function-calling
sql
database
data-visualization
matplotlib
json
conversational
chat
instruct
Eval Results
text-generation-inference
Inference Endpoints
| language: | |
| - en | |
| license: llama3.1 | |
| tags: | |
| - fireplace | |
| - fireplace-2 | |
| - valiant | |
| - valiant-labs | |
| - llama | |
| - llama-3.1 | |
| - llama-3.1-instruct | |
| - llama-3.1-instruct-8b | |
| - llama-3 | |
| - llama-3-instruct | |
| - llama-3-instruct-8b | |
| - 8b | |
| - function-calling | |
| - sql | |
| - database | |
| - data-visualization | |
| - matplotlib | |
| - json | |
| - conversational | |
| - chat | |
| - instruct | |
| pipeline_tag: text-generation | |
| model_type: llama | |
| model-index: | |
| - name: Llama3.1-8B-Fireplace2 | |
| results: | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: IFEval (0-Shot) | |
| type: HuggingFaceH4/ifeval | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: inst_level_strict_acc and prompt_level_strict_acc | |
| value: 54.83 | |
| name: strict accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: BBH (3-Shot) | |
| type: BBH | |
| args: | |
| num_few_shot: 3 | |
| metrics: | |
| - type: acc_norm | |
| value: 24.07 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MATH Lvl 5 (4-Shot) | |
| type: hendrycks/competition_math | |
| args: | |
| num_few_shot: 4 | |
| metrics: | |
| - type: exact_match | |
| value: 5.82 | |
| name: exact match | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: GPQA (0-shot) | |
| type: Idavidrein/gpqa | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: acc_norm | |
| value: 5.15 | |
| name: acc_norm | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MuSR (0-shot) | |
| type: TAUR-Lab/MuSR | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: acc_norm | |
| value: 4.38 | |
| name: acc_norm | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MMLU-PRO (5-shot) | |
| type: TIGER-Lab/MMLU-Pro | |
| config: main | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 15.63 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-Fireplace2 | |
| name: Open LLM Leaderboard | |
|  | |
| Fireplace 2 is a chat model, adding helpful structured outputs to Llama 3.1 8b Instruct. | |
| - an expansion pack of supplementary outputs - request them at will within your chat: | |
| - Inline function calls | |
| - SQL queries | |
| - JSON objects | |
| - Data visualization with matplotlib | |
| - Mix normal chat and structured outputs within the same conversation. | |
| - Fireplace 2 supplements the existing strengths of Llama 3.1, providing inline capabilities within the Llama 3 Instruct format. | |
| ## Version | |
| This is the **2024-07-23** release of Fireplace 2 for Llama 3.1 8b. | |
| We're excited to bring further upgrades and releases to Fireplace 2 in the future. | |
| Help us and recommend Fireplace 2 to your friends! | |
| ## Prompting Guide | |
| Fireplace uses the [Llama 3.1 Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) prompt format. The example script below can be used as a starting point for general chat with Llama 3.1 and also includes the different special tokens used for Fireplace 2's added features: | |
| import transformers | |
| import torch | |
| model_id = "ValiantLabs/Llama3.1-8B-Fireplace2" | |
| pipeline = transformers.pipeline( | |
| "text-generation", | |
| model=model_id, | |
| model_kwargs={"torch_dtype": torch.bfloat16}, | |
| device_map="auto", | |
| ) | |
| messages = [ | |
| {"role": "system", "content": "You are Fireplace, an expert technical assistant."}, | |
| {"role": "user", "content": "Hi, can you explain local area networking to me?"}, #general Llama 3.1 chat | |
| #{"role": "user", "content": "I have the following SQL table: employees (job_id VARCHAR, salary INTEGER)\n\nCan you find all employees with a salary above $75000?<|request_sql|>"}, #for SQL query | |
| #{"role": "user", "content": "{""name"": ""get_news_headlines"",""description"": ""Get the latest news headlines"",""parameters"": {""type"": ""object"",""properties"": {""country"": {""type"": ""string"",""description"": ""The country for which news headlines are to be retrieved""}},""required"": [""country""]}}\n\nHi, can you get me the latest news headlines for the United States?<|request_function_call|>"}, # for function call | |
| #{"role": "user", "content": "Show me an example of a histogram with a fixed bin size. Use attractive colors.<|request_matplotlib|>"}, #for data visualization | |
| #{"role": "user", "content": "Can you define the word 'presence' for me, thanks!<|request_json|>"}, #for JSON output | |
| ] | |
| outputs = pipeline( | |
| messages, | |
| max_new_tokens=512, | |
| ) | |
| print(outputs[0]["generated_text"][-1]) | |
| While Fireplace 2 is trained to minimize incorrect structured outputs, they can still occur occasionally. Production uses of Fireplace 2 should verify the structure of all model outputs and remove any unneeded components of the output. | |
| For handling of function call responses, use the [Llama 3.1 Instruct tool response style.](https://huggingface.co/blog/llama31#custom-tool-calling) | |
| ## Special Tokens | |
| Fireplace 2 utilizes special tokens applied to the Llama 3.1 tokenizer: | |
| - <|request_json|> | |
| - <|start_json|> | |
| - <|end_json|> | |
| - <|request_sql|> | |
| - <|start_sql|> | |
| - <|end_sql|> | |
| - <|request_matplotlib|> | |
| - <|start_matplotlib|> | |
| - <|end_matplotlib|> | |
| - <|request_function_call|> | |
| - <|start_function_call|> | |
| - <|end_function_call|> | |
| These are supplemental to the existing special tokens used by Llama 3.1, such as <|python_tag|> and <|start_header_id|>. Fireplace 2 has been trained using the Llama 3.1 Instruct chat structure, with new special tokens added within the conversation. | |
| The 'request' tokens are used by the user to request a specific type of structured output. They should be appended to the end of the user's message and can be alternated with normal chat responses throughout the conversation. | |
| ## The Model | |
| Fireplace 2 is built on top of Llama 3.1 8b Instruct. | |
| This version of Fireplace 2 uses data from the following datasets: | |
| - [glaiveai/glaive-function-calling-v2](https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2) | |
| - [b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context) | |
| - [sequelbox/Cadmium](https://huggingface.co/datasets/sequelbox/Cadmium) | |
| - [sequelbox/Harlequin](https://huggingface.co/datasets/sequelbox/Harlequin) | |
| - [migtissera/Tess-v1.5](https://huggingface.co/datasets/migtissera/Tess-v1.5) | |
| - [LDJnr/Pure-Dove](https://huggingface.co/datasets/LDJnr/Pure-Dove) | |
| Additional capabilities will be added to future releases. | |
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) | |
| Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ValiantLabs__Llama3.1-8B-Fireplace2) | |
| | Metric |Value| | |
| |-------------------|----:| | |
| |Avg. |18.31| | |
| |IFEval (0-Shot) |54.83| | |
| |BBH (3-Shot) |24.07| | |
| |MATH Lvl 5 (4-Shot)| 5.82| | |
| |GPQA (0-shot) | 5.15| | |
| |MuSR (0-shot) | 4.38| | |
| |MMLU-PRO (5-shot) |15.63| | |
|  | |
| Fireplace 2 is created by [Valiant Labs.](http://valiantlabs.ca/) | |
| [Check out our HuggingFace page for Shining Valiant 2 and our other models!](https://huggingface.co/ValiantLabs) | |
| [Follow us on X for updates on our models!](https://twitter.com/valiant_labs) | |
| We care about open source. | |
| For everyone to use. | |
| We encourage others to finetune further from our models. | |