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Model Sources [optional]
Repository:
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Paper [optional]:
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Demo [optional]:
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Uses
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
[More Information Needed]
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:
quant_method: bitsandbytes
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 0.6.0
Runs of Chat-Error mistral on huggingface.co
5
Total runs
-1
24-hour runs
-1
3-day runs
-1
7-day runs
-1
30-day runs
More Information About mistral huggingface.co Model
mistral huggingface.co
mistral huggingface.co is an AI model on huggingface.co that provides mistral's model effect (), which can be used instantly with this Chat-Error mistral model. huggingface.co supports a free trial of the mistral model, and also provides paid use of the mistral. Support call mistral model through api, including Node.js, Python, http.
mistral huggingface.co is an online trial and call api platform, which integrates mistral's modeling effects, including api services, and provides a free online trial of mistral, you can try mistral online for free by clicking the link below.
Chat-Error mistral online free url in huggingface.co:
mistral is an open source model from GitHub that offers a free installation service, and any user can find mistral on GitHub to install. At the same time, huggingface.co provides the effect of mistral install, users can directly use mistral installed effect in huggingface.co for debugging and trial. It also supports api for free installation.