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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
The following
bitsandbytes
quantization config was used during training:
load_in_8bit: True
load_in_4bit: False
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: fp4
bnb_4bit_use_double_quant: False
bnb_4bit_compute_dtype: float32
Framework versions
PEFT 0.6.3.dev0
Runs of kings-crown EM624_QA_Full on huggingface.co
0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
More Information About EM624_QA_Full huggingface.co Model
EM624_QA_Full huggingface.co
EM624_QA_Full huggingface.co is an AI model on huggingface.co that provides EM624_QA_Full's model effect (), which can be used instantly with this kings-crown EM624_QA_Full model. huggingface.co supports a free trial of the EM624_QA_Full model, and also provides paid use of the EM624_QA_Full. Support call EM624_QA_Full model through api, including Node.js, Python, http.
EM624_QA_Full huggingface.co is an online trial and call api platform, which integrates EM624_QA_Full's modeling effects, including api services, and provides a free online trial of EM624_QA_Full, you can try EM624_QA_Full online for free by clicking the link below.
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EM624_QA_Full is an open source model from GitHub that offers a free installation service, and any user can find EM624_QA_Full on GitHub to install. At the same time, huggingface.co provides the effect of EM624_QA_Full install, users can directly use EM624_QA_Full installed effect in huggingface.co for debugging and trial. It also supports api for free installation.