openhands-lm-32b-v0.1OpenHands
32.8B Params FP8 Open Weights

OpenHands/openhands-lm-32b-v0.1 is a 32 billion parameter open coding model developed by OpenHands, built upon Qwen Coder 2.5 Instruct 32B. It features a 128K token context window and is specifically fine-tuned using an RL-based framework on OpenHands-generated data from diverse open-source repositories. This model achieves a 37.2% resolve rate on SWE-Bench Verified, demonstrating strong performance on software engineering tasks comparable to models with significantly more parameters.

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Parameters:32.8BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:March 2025
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all-hands/openhands-lm-32b-v0.1
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.

1

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

1

top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

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.

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.

1

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.