Salesforce/xLAM-2-3b-fc-r
The Salesforce xLAM-2-3b-fc-r is a 3.1 billion parameter Large Action Model (LAM) developed by Salesforce, designed to translate user intentions into executable actions for AI agents. This model excels in multi-turn conversation and tool usage, trained using the novel APIGen-MT framework for high-quality data generation. It achieves state-of-the-art performance on BFCL and τ-bench benchmarks, outperforming larger models in function-calling and agentic capabilities, making it ideal for automating complex workflows.
Hugging Face Popular Sampler Settings
Most commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
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top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
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top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
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frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
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repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
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min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.
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